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About us: Behind every innovative new medical device, new healthcare policy, and research into new treatments, there?s a literature review. At DistillerSR Inc., we?re changing the way that scientific research is conducted. Founded in 2008, DistillerSR is the world?s leading AI-enabled workflow automation and evidence management platform for streamlining the production of critical literature-based health research. DistillerSR is used by 80% of the top 10 global medical device and pharmaceutical companies to inform life-changing product research, prepare regulatory submissions and to monitor for safety issues with medical products once in market. At DistillerSR, we have three core values: Always Leading, Always Innovating, and Always Trusted. Our amazing team lives these values every day and our customers trust us to bring them innovative, world-leading solutions that power their important work. Scope of the Role: The Customer Success Manager drives customer engagement and retention. CSMs advise and guide our customers as they map their business needs to the capabilities of DistillerSR, with the goal of ensuring customers adopt the DistillerSR platform deeply and derive the best value from their DistillerSR subscriptions and services. CSMs collaborate cross-functionally with other DistillerSR departments to identify opportunities and risk, and to develop recommendations and solutions. Duties & Responsibilities: Relationships & Engagement Build and maintain strong relationships with customers to drive long-term customer success and value. Engage with customers regularly, promoting and measuring customers? engagement with the platform as a lever to account retention. Conduct regular ROI meetings with customers to assess value delivered and identify areas for improvement. Align actions and decisions with DistillerSR?s core organizational values to foster a culture of customer excellence. Consultation Promote customer satisfaction through application of product knowledge and technical expertise. Recommend best-practice uses of DistillerSR based on understanding of the customer?s business, use cases, success criteria for getting value, and data. Collect key business and user insights, developing strategic plans and a long-term vision for customer accounts. Participate in client requirements-gathering workshops, documenting feedback. Advocate with DSR internal stakeholders for customer needs in product evolution. Adoption, Retention, and Expansion Facilitate the onboarding of new customers, supporting customer change management initiatives to adopt DistillerSR. Monitor customer usage data and act upon it to resolve product use inefficiencies. Identify opportunities to increase product usage. Proactively identify at-risk customers. Develop and implement retention plans, maintaining internal visibility through regular updates. Supplement the first line of support when necessary, helping customers resolve issues. Identify customer expansion opportunities for action by the broader account team, specifically including the Account Executive. Support Sales activities such as conducting product demonstrations, participating in client discussions, and RFP processes. Continuous Improvement Participate in continuous improvement initiatives as required and assist with drafting service-related policies, procedures, and work instructions. Key Contacts Frequent interaction with assigned customers and target clients, including leadership and individual contributors, with both business and technical roles. Collaborates closely with all members of Customer Success, Sales, Global Support, Professional Services, Marketing, and P

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Summary: This job will lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences. Job Description: Essential Responsibilities: Lead the development and optimization of advanced machine learning models. Oversee the preprocessing and analysis of large datasets. Deploy and maintain ML solutions in production environments. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models, making necessary adjustments. Minimum Qualifications: 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Additional Responsibilities & Preferred Qualifications: Subsidiary: PayPal Travel Percent: 0 The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: Primary Location : Pay Range: San Jose, California: ($196,500.00 - $291,500.00 Annually) Additional Location(s) : Pay Range: No other locations are assigned to this requisition currently. Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable. PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing—physical, emotional, and financial—delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health. Who We Are: Click Here to learn more about our culture and community. Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.

EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more. We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at www.evenuplaw.com. Machine Learning Engineer We're looking for a Machine Learning Engineer to join our ML team at EvenUp. You'll develop and deploy models that power Piai™, our proprietary claims-intelligence platform, with a focus on machine learning, natural-language processing, and generative AI. Working alongside senior ML engineers, data scientists, and legal subject-matter experts, you'll turn raw legal and medical data into production-ready models that directly improve outcomes for personal-injury clients. What You'll Do Explore, implement, and benchmark ML, NLP, and generative AI methods - including LLM fine-tuning, retrieval-augmented generation, and document understanding. Clean, annotate, and transform structured and unstructured case data, and build reusable datasets and data loaders. Design experiments, run A/B tests, analyze results, and communicate findings to product and engineering teams. Help integrate models into our production systems, partnering with ML platform engineers on testing, monitoring, and scaling. Pair with product managers, legal analysts, and software engineers to translate real problems into ML solutions and measurable improvements. Stay current with research in LLMs, representation learning, and prompt engineering, and share what you learn with the team. What You Bring B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a related field. Solid grounding in ML fundamentals - supervised and unsupervised learning, evaluation metrics, overfitting and regularization. Hands-on experience with NLP or generative AI techniques - transformers, embeddings, sequence-to-sequence models, or LLMs. Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, or spaCy. Familiarity with SQL and basic data engineering concepts - ETL, versioned datasets, notebooks. Strong analytical thinking, clear communication, and eagerness to learn and iterate quickly in a fast-moving startup. Ability to work hybrid (3 days your choice) in our San Francisco or Toronto, Canada office. Nice to Have Exposure to cloud platforms (AWS, GCP). Experience with experiment-tracking tools (Weights & Biases, Gemini Enterprise Agent Platform, MLflow). Familiarity with containerized deployment (Docker, Kubernetes). Experience in a high-growth startup environment. Benefits & Perks: As part of our total rewards package, we offer attractive benefits and perks to our employees, including: Choice of medical, dental, and vision insurance plans for you and your family. Additional insurance coverage options for life, accident, or critical illness. Flexible paid time off, sick leave, short-term and long-term disability. 10 US observed holidays, and Canadian statutory holidays by province. A home office stipend. 401(k) for US-based employees and RRSP for Canada-based employees. Paid parental leave. A local in-person meet-up program. Hubs in San Francisco and Toronto. (Please note the above benefits & perks are for full-time employees) Notice to Candidates: To ensure fairness and proper consideration, we do not accept resumes or expressions of interest via email or social media messages. If you're interested in a role, please submit your application directly through our careers page . Please note that EvenUp may use AI notetakers and other recording devices in the recruiting process. If you interview with us, with your consent, we may record your conversations and summarize them into notes for internal use. Recording is optional, and declining will not affect your candidacy. EvenUp is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Compensation Range: $130K - $205K

Join the Dealer Tech division within Capital One's Financial Services Technology group, where we develop and support cutting edge technological solutions that streamline the auto financing process for dealers. Our team focuses on creating integrated, secure, and user friendly platforms that enhance dealer operations and customer experiences, ensuring compliance with the latest financial regulations. This pivotal role supports business growth and fosters strong dealer relationships, making every transaction smoother and more efficient. Dealer Tech within Financial Services Technology at Capital One is specifically designed to address the technological needs of auto dealers who partner with Capital One. This division focuses on developing and maintaining systems that facilitate the smooth operation of auto financing, from loan origination to funding. Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 3 years of experience programming with Python, Java, Golang, or C++ At least 2 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 3 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 1 year of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 1+ years of experience optimizing ML algorithms, configurations, and infrastructure 1+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 1+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 1+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) Authored/co-authored a paper on a ML technique, model, or proof of concept 1+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $161,800 - $184,600 for Machine Learning Engineer 3 New York, NY: $176,500 - $201,400 for Machine Learning Engineer 3 Plano, TX: $147,100 - $167,900 for Machine Learning Engineer 3 Richmond, VA: $147,100 - $167,900 for Machine Learning Engineer 3 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Analytics Engineer About Sprinter Health At Sprinter Health, our mission is reimagining how people access care by bringing it directly to their homes. Nearly 30% of patients in the U.S. skip preventive or chronic care simply because they can't get to a doctor's office. For many, the ER becomes their first touchpoint with the healthcare system, driving over $300B in avoidable costs every year. By using the same technologies that power leading marketplace and last-mile platforms, we deliver care where people are, especially those who need it most. So far, we've supported more than 2 million patients across 22 states, completed 130,000+ in-home visits, and maintained a 92 NPS. Our team of clinicians, technologists, and operators has raised over $125M from investors like a16z, General Catalyst, GV, and Accel and enjoys multi-year runway. About The Role We're looking for an Analytics Engineer to build the trusted data layer that analysts, data scientists, operations, finance, product, and our payer customers depend on. At Sprinter, data is central to how we operate, measure performance, serve patients, and support our health plan partners. This role will own the canonical models, metric definitions, transformation logic, documentation, and tests that make our data reliable and reusable across the company. You'll help define what each table, field, and metric means, then build the infrastructure that ensures those definitions are consistently applied. That includes modeling data in dbt or equivalent tooling, creating reporting-ready tables, improving lineage and documentation, reconciling metrics across teams, and helping prevent the kind of data drift and metric chaos that slows companies down as they scale. This role is ideal for someone who treats metric definitions as product artifacts, thinks in contracts and tests, and cares deeply about making data trustworthy for both internal users and external customers. Office Location We are a hybrid company based in the Bay Area with offices in both San Francisco and Menlo Park. We operate on a hybrid schedule, working from the office Monday through Thursday, with Fridays designated as work-from-anywhere days. We care deeply about work-life balance and are happy to provide flexibility when life happens. We ask that employees be in the office Monday through Thursday to collaborate with their teams while maintaining flexibility where it matters most. Lunch is provided every day, and the entire team takes an hour to eat together. It's one of the ways we stay connected outside of meetings. You'll usually find us playing a board game before getting back to work. What you will do Build canonical data models that create a shared source of truth across the company Define and maintain core business, operational, financial, product, and customer-facing metrics Model data in dbt or equivalent transformation tooling so dashboards, self-serve analytics, and customer reports pull from trusted tables Write tests, documentation, and data quality checks that catch issues before they reach users Create clear definitions for tables, fields, and metrics so teams understand what the data means and when to use it Reconcile metric definitions across internal teams, external reporting needs, and payer customer expectations Trace data lineage and debug dashboards, reports, or tables that change unexpectedly Partner with analysts, data scientists, operations, finance, product, engineering, and customer-facing teams to understand data needs and translate them into reliable models Help build reusable reporting frameworks that make onboarding new payers faster and less manual Partner with the data platform team to evolve warehouse tables, improve data architecture, and strengthen data contracts Improve warehouse cost, performance, and maintainability Support PHI-aware data access patterns and help ensure sensitive healthcare data is modeled and used responsibly What you have done Built analytics engineering, business intelligence, or data modeling systems in a production cloud warehouse environment Written expert-level SQL and designed data models that support reporting, analysis, and decision-making Worked with dbt or an equivalent transformation framework Built tested, documented, reusable data models rather than one-off queries Defined, maintained, or reconciled business-critical metrics across teams Partnered with analysts, data scientists, operators, finance teams, product teams, or customer-facing stakeholders Debugged data quality issues, dashboard changes, metric discrepancies, and lineage problems Worked with cloud data warehouses such as BigQuery, Snowflake, Redshift, Databricks SQL, or similar Balanced speed, correctness, usability, and maintainability when building data assets Communicated clearly with technical and non-technical stakeholders about what data means and how it should be used What gives you an edge You have experience with healthcare data, claims data, EHR data, payer data, provider data, or other complex healthcare datasets You've worked with PHI, HIPAA-aware data access patterns, or other sensitive regulated data You have experience building customer-facing reporting, embedded analytics, or multi-tenant data models You've worked with row-level security, access controls, or governed self-serve analytics You have experience using Python for analysis, scripting, data validation, or automation You've helped establish a semantic layer, metrics layer, or company-wide source of truth You've built data models in a high-growth startup or operationally complex environment You have experience improving warehouse performance, cost, and query efficiency What makes you successful You treat a metric definition as a product artifact, not a Slack thread You make data trustworthy, reusable, and easy to understand You prevent metric chaos by building clear definitions, tests, and documentation You build so that a fix in one place does not require five copy-paste edits elsewhere You understand that internal users and external customers both need data they can trust You care about the usability of the data model, not just whether the pipeline runs You can explain data discrepancies clearly and drive teams toward shared definitions You build foundations that help the company move faster with more confidence Day to Day In This Role, You Might Spend Your Time Building or refactoring dbt models Adding tests to core tables Defining canonical fields and documenting how they should be used Reviewing metric definitions and reconciling them across teams Debugging a dashboard, report, or customer-facing metric that changed unexpectedly Tracing lineage from source systems through warehouse models to downstream reports Partnering with analysts, operators, finance, product, or customer-facing teams on reporting needs Improving warehouse performance, cost, and maintainability Designing reusable reporting structures that make new payer launches easier The Interview Process We aim to complete the interview process within 2–3 weeks. It will usually consist of: Recruiter Screen: Background fit, motivation, and compensation alignment Hiring Manager Interview: Analytics engineering experience, data modeling depth, and stakeholder partnership Hands-on Technical Assessment: SQL, data modeling, metric design, and practical analytics engineering judgment Onsite Interview: Technical case study, systems/data modeling discussion, behavioral interview, and lunch with the team References: Validation of performance, judgment, and working style What we offer Meaningful pre-IPO equity Medical, dental, and vision plans 100% paid for you and your dependents Flexible PTO + 10 paid holidays per year 401(k) with match 16-week parental leave policy for birthing parent, 8 weeks for all other parents HSA + FSA contributions Life insurance, plus short and long-term disability coverage Free daily lunch in-office Annual learning stipend Relocation assistance Equal Opportunity Statement Sprinter Health is an equal opportunity employer. We value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other protected classes. Beware of recruitment fraud and scams that involve fictitious job descriptions followed by false job offers. If you are applying for a job, you can confirm the legitimacy of a job posting by viewing current open roles on our official Sprinter Health Careers website. All legitimate job postings will require an application to be made directly on our official Sprinter Health Careers website. Job-related communications will only be sent from email addresses ending in @sprinterhealth.com. Please ensure that you're only replying to emails that end with @sprinterhealth.com.

Job Requisition ID # 26WD101381 Position Overview Autodesk's worldwide sales organization depends on its forecast, pipeline, targets and reporting. This role builds the data models behind them. As an Analytics Engineer on the Forecasting & Revenue Intelligence team, you turn sales, subscription and hierarchy data into tested, documented models that analysts and sales leaders can trust, covering what customers bought, who owns which accounts and how the sales organization looked on any given date. You will work in SQL and dbt on Snowflake, and you will work closely with the people who use your models. This is a hands-on role on a new team, and you will own what you ship. Location: United States (remote). Central or Eastern time zone preferred. Organization: Revenue Operations Responsibilities Build and maintain dbt models on Snowflake that bring Salesforce, subscription, billing, hierarchy and forecast data into a clean, documented form Model data for analysis: a clear grain, stable keys, and definitions consistent with the shared metric dictionary Keep history so any published number can be reproduced as it stood on the day it went out Maintain the mapping between accounts, territories, sellers and the sales hierarchy as the organization changes Reconcile the data to Salesforce and to Finance, and find the cause when they disagree Build the datasets behind the weekly forecast pack, business reviews and leadership dashboards Add tests and monitoring for freshness, completeness and accuracy, and fix what breaks Explain data issues and trade-offs to sales and finance partners in plain terms, and agree on a fix with them Work in version control with code review and continuous integration Minimum Qualifications Bachelor's degree in a technical or quantitative field, or equivalent practical experience 3+ years in analytics engineering, data engineering or BI development, building models other people depended on Dbt in production, with tests and documentation as part of how you work Strong SQL, including window functions and incremental models, in a cloud data warehouse such as Snowflake Working knowledge of the Salesforce data model: accounts, opportunities, line items and ownership Ability to explain a data problem to a non-technical stakeholder and reach a decision together Preferred Qualifications Dbt snapshots or slowly changing dimensions for point-in-time reporting Python for transformation or orchestration, with Airflow or similar Enterprise software or SaaS commercial data: subscriptions, renewals, territories, and direct and partner routes to market Revenue intelligence platforms such as Clari, Gong or Aviso, and BI tools such as Power BI, Tableau or Sigma Experience as an early hire on a new data team Learn More About Autodesk Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk – it's at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world. When you're an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us! Benefits From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/ Salary transparency Salary is one part of Autodesk's competitive compensation package. For U.S.-based roles, we expect a starting base salary between $103,000 and $185,130. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package. Equal Employment Opportunity At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law. Belonging We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging In-Person Onboarding and Identity Verification This role may require in-person onboarding and/or in-person ID verification.

Dexis is a dynamic professional services firm dedicated to partnering with government and community leaders both in the U.S. and internationally to achieve critical social outcomes in a rapidly changing world. At Dexis, you will experience a corporate culture of inclusiveness, respect, fairness, and trust. You will be given the means and mentorship needed to succeed, and your creativity will be rewarded. About The Position Dexis is recruiting a Senior Data Analyst to support anticipated programming with the Department of State (DOS). This opportunity will provide policy direction and oversight in the areas of international security, security assistance, military operations, and defense strategy and plans, specifically focused on Foreign Military Financing (FMF) and International Military Education and Training (IMET) military grant assistance programs. Candidates must have an active Secret Clearance. This position is contingent upon contract award. Responsibilities Providing quantitative analytical support to produce country papers and perform data quality checks to ensure integrity of the data. Coordinating with the client and with the core M&E team regarding additional data points to consider and explore for further analysis. Designing and populating easy to read and digestible mockups of data visualization options to present to the client. Documenting data calculation steps and methodologies applied to the analysis as needed. Analyzing country trends for regional and global comparisons. Producing approved final data visualizations of the countries to be included in reports. Adapting to changing needs of the project and the team as needed. Qualifications Bachelor's degree in relevant field of study and at least six (6) years of data analytics experience. Active Secret Clearance required. Expertise aggregating, normalizing, and displaying data from multiple sources, and conveying nuanced distinctions and conclusions to end users while ensuring utmost accuracy. Experience applying quantitative research methods, operating or managing databases, and applying statistical methods to conduct analysis. Ability to perform advanced quantitative analyses of structured and unstructured data, especially working with, and manipulating large data sets in Excel. Ability to work independently and meet deadlines with minimal supervision. Experience designing data visualizations to demonstrate data trends. Comfortable with the changing needs of the client and the team. Strong attention to detail. Preferred Requirements Experience creating data dashboards using tools such as Tableau or Flourish. Experience building APIs. Prior experience with DOS programming. Below is the pay range aligned with this position. When developing a range, Dexis evaluates compensation holistically, triangulating between external market research, our budget for the position, and internal equity to arrive at a figure that is fair and competitive. Offers within this range will be based on an individual candidate's qualification, relevant education and experience, skills, performance, and organizational needs. Dexis Pay Range For This Role $105,000—$155,000 USD Benefits Dexis offers benefits to support employees' health, financial security, and well-being. The benefits outlined below are for full-time, US-based positions only. These benefits include: Medical and prescription drug coverage: A choice of three UnitedHealthcare medical plans, with coverage options for employees and eligible dependents. Dental insurance: Dental coverage for employees and eligible dependents, including preventive, basic, major, and orthodontic services, subject to plan limits. Company-paid vision insurance: Vision coverage for employees and eligible dependents, with premiums paid in full by Dexis. Employer-funded health reimbursement arrangement (HRA): Employees who enroll in the Silver HRA medical plan receive an employer-funded HRA to help pay eligible in-network deductible expenses. Company-paid life and disability insurance: Basic life and accidental death and dismemberment (AD&D) insurance, plus short-term and long-term disability coverage. Optional supplemental insurance: Voluntary supplemental life and AD&D insurance options, including life insurance options for eligible dependents. Employee Assistance Program (EAP): Company-paid access to confidential counseling and legal and financial support resources for employees and their families. Health and wellness resources: Virtual care, behavioral health resources, and wellness programs available through the medical plan. Benefits assistance: Personalized support with benefit enrollment, coverage questions, claims, and finding providers through the Employee Care Center. Participation, coverage, and employee contributions are subject to applicable benefit plan terms and eligibility requirements. Dexis is on a mission to help solve today's most pressing global political, social, and economic challenges and create a world where all people are safe and prosperous. As a Dexis employee, you will be challenged, empowered, and mentored. Our motto is "find a way or make a way" — that's how Dexis goes "all in." How will you? If you are passionate about this opportunity, apply now! Only those applicants who meet the above criteria will be contacted for interview. Dexis is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, sex, national origin, religion, pregnancy, disability, age, genetic information, military service, veteran status, ethnicity, citizenship, sexual orientation, gender identity, marital status, childbirth and related medical conditions, including lactation, or any other protected class under applicable law.

Description Leidos has a new and exciting opportunity for a Data Analyst in our Intel Sector Analysis Solutions Business Area (ASBA) in McLean, VA. Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in Analysis Solutions Business Area! Job Summary The Data Analyst will provide enterprise‑level analytical support by generating groupwide metrics, improving knowledge‑management processes, and ensuring data accuracy across multiple systems. The Analyst will develop data visualizations using Tableau, Power BI, or Excel to communicate insights clearly to non‑technical customers and stakeholders. This role supports a small team of Intel Analysts in a dynamic, fast‑paced environment and requires the ability to operate independently with minimal guidance. Responsibilities Include Pull, compile, and analyze groupwide metrics to support leadership decision‑making Identify data bottlenecks and recommend process improvements to streamline knowledge‑management workflows Clean, standardize, and validate datasets from multiple sources Develop dashboards, reports, and visualizations using Tableau, Power BI, or Excel Brief findings and trends to non‑technical customers, leadership, and stakeholders Build analytical models to identify patterns, track performance, and forecast trends Collaborate with Intel Analysts to translate operational needs into data‑driven insights Maintain documentation of data sources, processes, and analytical methodologies Operate effectively in a dynamic environment with shifting priorities Work independently with limited direction while meeting deadlines and quality expectations Qualifications BS and 4 – 8 years of prior relevant experience or Masters with 2 – 6 years of prior relevant experience. Experience may be exchanged for degree requirements Requires an active TS/SCI with Polygraph Strong knowledge of Python for data cleaning, transformation, and modeling Knowledge of all‑source intelligence production, including SIGINT and/or HUMINT reporting Ability to identify and recommend process improvements Experience creating data models that depict trends and support decision‑making Proficiency with data visualization tools (Tableau, Power BI, or Excel) Strong communication skills, with the ability to brief non‑technical audiences Ability to work in a dynamic environment and adapt to evolving mission requirements Proven ability to work independently without constant direction Strong organizational and problem‑solving skills If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else #ASBA If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares. Original Posting October 21, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range Pay Range $73,450.00 - $132,775.00 The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law. About Leidos Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. Headquartered in Reston, Virginia, with 47,000 global employees, Leidos reported annual revenues of approximately $16.7 billion for the fiscal year ended January 3, 2025. For more information, visit www.Leidos.com. Pay And Benefits Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at www.leidos.com/careers/pay-benefits. Securing Your Data Beware of fake employment opportunities using Leidos' name. Leidos will never ask you to provide payment-related information during any part of the employment application process (i.e., ask you for money), nor will Leidos ever advance money as part of the hiring process (i.e., send you a check or money order before doing any work). Further, Leidos will only communicate with you through emails that are generated by the Leidos.com automated system – never from free commercial services (e.g., Gmail, Yahoo, Hotmail) or via WhatsApp, Telegram, etc. If you received an email purporting to be from Leidos that asks for payment-related information or any other personal information (e.g., about you or your previous employer), and you are concerned about its legitimacy, please make us aware immediately by emailing us at LeidosCareersFraud@leidos.com. If you believe you are the victim of a scam, contact your local law enforcement and report the incident to the U.S. Federal Trade Commission. Commitment to Non-Discrimination All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! The work: The Senior Data Analyst will analyze large and complex datasets, develop data visualizations, build dashboards, and produce clear analytical reports to support data‑driven decision‑making for a federal client. The role requires strong data manipulation, SQL querying, and experience with modern visualization tools. Key Responsibilities: Analyze complex datasets to identify trends, patterns, and insights. Develop dashboards and visualizations using Databricks, Tableau, Power BI, and MS Excel. Prepare detailed analytical reports and recommendations for stakeholders. Conduct data cleaning, manipulation, and transformation of large datasets. Query databases using SQL for data extraction and analysis. Apply predictive analytics or machine‑learning techniques when appropriate. Participate in agile delivery processes, including user story documentation and testing. Here is what you need: US Citizen (Public Trust eligibility) Proficiency in Databricks, Tableau, Power BI, and MS Excel for data visualization. Strong SQL skills for database querying. Experience with data cleaning, manipulation, and transformation. Ability to analyze large datasets and communicate insights clearly. Experience producing dashboards and data‑driven reports. Familiarity with agile methodologies and software development lifecycle practices. Preferred experience: Experience with statistical analysis tools (R, SPSS). Exposure to predictive analytics or machine‑learning frameworks. Experience with correlation analysis and advanced data‑quality techniques. Additional Databricks experience (pipelines, transformations) As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia . The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply. The pay range for the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia is: $103,200—$196,400 USD What We Believe As a company wholly dedicated to serving the US federal government, we bring together the best talent to help reinvent how federal agencies operate and deliver greater value for their mission and the American people. We have an unwavering commitment to creating a culture in which all our people are respected, feel a sense of belonging, and have equal opportunity. As a business imperative, every person at Accenture Federal Services has the responsibility to create and sustain a culture where everyone feels welcomed and included. This is grounded in our core values and our experience that hiring and developing great people who reflect different perspectives, experiences, and backgrounds is key to driving innovation and delivering the results that our clients and the country count on. Equal Employment Opportunity Statement We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. For details, view a copy of the Accenture Federal Services Equal Opportunity Policy Statement. Accenture Federal Services is an Equal Employment Opportunity employer. Additionally, as an Affirmative Action Employer for Veterans and Individuals with Disabilities, Accenture Federal Services is committed to providing veteran employment opportunities to our service men and women. Requesting An Accommodation Accenture Federal Services is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture Federal Services and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired. If you are being considered for employment opportunities with Accenture Federal Services and need an accommodation for a disability or religious observance during the interview process or for the job you are interviewing for, please speak with your recruiter. Other Employment Statements Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States. Candidates who are currently employed by a client of Accenture Federal Services or an affiliated Accenture business may not be eligible for consideration. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information. California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please click here for additional important information.

Description The Amazon Security Experiences (ASE) organization is the data intelligence backbone of Amazon Security. We build and operate the data platform that powers security insights, builder experience analytics, and tooling decisions across Amazon's security ecosystem. Every insight surfaced to security leadership, from builder productivity trends to security issue quality metrics, flows through systems our team designs, builds, and maintains. We operate at scale, processing large volumes of security and operational data daily through hundreds of pipelines consisting of transformations, reporting queries, ingestions, and infrastructure management scripts. Our engineers work directly with source systems across AWS and SDO (Security, Developer, and Operations) data domains to procure data, convert it into structured formats, build large-scale processing pipelines, design analytical data models, and maintain infrastructure with the highest security and compliance standards. We are seeking a Data Engineer I to join our Security Data Intelligence (SDI) team. In this role, you will build and maintain data pipelines that power security analytics across Amazon. Working with well-defined requirements and guidance from senior engineers, you will create physical data models, optimize data pipelines for defined datasets, and deliver reliable, well-documented solutions on schedule. You will partner with teams across ASE, BizOps, MapSec, and other security organizations to implement data ingestion flows and support analytical models that serve the broader Amazon Security organization. Key job responsibilities Learn and apply team-established data processing guidelines and best practices when building and testing pipelines. Measure and improve dataset quality across owned pipelines, identifying issues and proposing solutions to the team. Flag limitations or opportunities in data processing tools to senior engineers for evaluation. Learn and understand the team's existing data architecture, including how security data flows through ingestion, transformation, and serving layers. Build data solutions at the component level within the established team data architecture, following defined logical data models. Create physical data models for assigned datasets, applying appropriate persistence and integration techniques. Understand the implications of implementation decisions (e.g., normalization, distribution) and seek guidance from senior engineers on trade-offs. Write secure, stable, testable, and maintainable code with minimal defects, following team coding standards. Clearly document solutions for ease of use and maintainability by teammates and data consumers. Get all data models, pipeline designs, and code reviewed by senior engineers before deployment. Test code thoroughly and understand the maintenance characteristics, runtime properties, and dependencies of delivered solutions. Build and maintain data pipeline infrastructure for assigned datasets using team-established patterns and tools. Apply basic database optimization techniques such as partitioning, distribution, and indexing as directed. Understand the underlying system infrastructure that data solutions depend on, including differences between data persistence solutions. Follow team guidelines for infrastructure management, security compliance, and automation practices. Solve straightforward, well-defined problems with guidance from senior engineers, for example, building ingestion pipelines for a new security data source where the schema and requirements are defined, or troubleshooting data quality issues in existing datasets by researching root causes and thoroughly resolving defects. Handle problems even outside your own domain by either resolving them or ensuring a clear hand-off to the right owner. Take well-defined requirements and deliver solutions on schedule within assigned scope. Participate in team design, scoping, and prioritization discussions to understand project context. Manage your own task execution effectively, seeking guidance when blocked or uncertain. Communicate progress and dependencies clearly to your team lead and senior engineers. Build good working relationships with teammates, peer engineers, and data consumers across ASE and SDO. Partner effectively with Business Analysts, Data Scientists, and peer SDEs to understand data requirements. Help train and mentor DE interns when applicable. Participate in the interview process. Recognize discordant views and participate in constructive dialogue with peers. Follow team-established best practices for data discovery, naming conventions, and data security. Classify, store, and handle data per Amazon security and compliance policies. Ensure proper access control, data integrity, and auditability for all produced datasets. Track security risks in data handling, mitigate issues, and escalate in a timely manner. Identify data quality issues and pipeline deficiencies in owned components and propose solutions to the team. Participate in code reviews, design discussions, and team planning sessions. Make small improvements to team development processes when directed. Actively seek knowledge of team data architecture and apply learnings to improve your data solutions. Participate in on-call rotation and respond to pipeline incidents following established runbooks and escalation procedures. Understand the maintenance characteristics, runtime properties, and dependencies of team data systems. Contribute to monitoring and alarming setup for owned pipelines with guidance from senior engineers. Document incident resolutions and contribute to runbook updates for owned components. Basic Qualifications 2+ years of data engineering experience Experience with data modeling, warehousing and building ETL pipelines Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) Experience with one or more scripting language (e.g., Python, KornShell) Preferred Qualifications Experience with big data technologies such as: Hadoop, Hive, Spark, EMR Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. USA, WA, Seattle - 101,300.00 - 160,000.00 USD annually Company Amazon.com Services LLC Job ID: A10582746

Costco Travel IT is responsible for the technical future of Costco Wholesale , the third largest retailer in the world with wholesale operations in fourteen countries. Despite our size and explosive international expansion, we continue to provide a family, employee centric atmosphere in which our employees thrive and succeed. This is an environment unlike anything in the high-tech world and the secret of Costco's success is its culture. The value Costco puts on its employees is well documented in articles from a variety of publishers including Bloomberg and Forbes. Our employees and our members come FIRST. Costco is well known for its generosity and community service and has won many awards for its philanthropy. The company joins with its employees to take an active role in volunteering by sponsoring many opportunities to help others. Come join the Costco Travel IT family . Costco IT is a dynamic, fast-paced environment, working through exciting transformation efforts. We are building the next generation retail environment where you will be surrounded by dedicated and highly professional employees. As a Build Engineer you work with Software Developers and DevOps Teams to ensure our products seamlessly move from development through rollout and into production. This requires scripting and coding with an eye toward scalability as we are pushing updates and iterating on all of our products. The Build Engineer will be responsible for designing, implementing, and maintaining our build and release infrastructure. This role is critical to ensuring efficient, reliable, and automated software builds across multiple platforms and environments. Our vision is to continuously improve build and configuration management tools as well as best practices to meet needs of scaling applications as well as growing engineering teams. If you want to be a part of one of the worldwide BEST companies "to work for" , simply apply and let your career be reimagined. ROLE Designing and developing solutions to improve developer experience and code velocity to production. Design, develop, and maintain automated build systems and continuous integration/continuous deployment (CI/CD) pipelines. Optimize build processes to reduce build times and improve efficiency. Monitor build systems and proactively resolve issues to minimize downtime. Implement and maintain build configurations across multiple platforms (Windows, Linux). Create and maintain build scripts, tools, and automation frameworks. Automate repetitive tasks to improve team productivity. Integrate third-party tools and services into the build pipeline. Maintain version control strategies and branching models. Provide technical support and troubleshooting for build-related issues. Document build processes, procedures, and best practices. Monitor and optimize build performance metrics Implement security best practices in build and deployment processes Manage build artifacts, dependencies, and package repositories Required 3+ years of experience in build engineering, DevOps, or related role. Strong experience with CI/CD platforms (Jenkins, Git, GitHub, Azure DevOps, or similar). Proven track record of implementing and maintaining automated build systems. Experience with version control systems, particularly Git. Proficiency in scripting languages (Python, Bash, PowerShell, Groovy). Strong understanding of build tools (Gradle, Maven, etc.). Experience with containerization technologies (Docker, Kubernetes) Recommended Strong problem-solving and analytical skills. Attention to detail and commitment to quality. Ability to debug complex build and deployment issues. Understanding of networking, security, and system administration concepts. Excellent communication skills, both written and verbal. Ability to work collaboratively in a team environment. Self-motivated with ability to work independently. Strong organizational and time management skills. Adaptability and willingness to learn new technologies. Proficient in Microsoft Workspace applications, including Outlook, Word, Excel, PowerPoint, and Teams. Successful internal candidates will have spent one year or more on their current team. Required Documents Cover Letter Resume California applicants, please click to review the Costco Applicant Privacy Notice. Pay Ranges Level 3 - $130,000 - $160,000 We offer a comprehensive package of benefits including paid time off, health benefits - medical/dental/vision/hearing aid/pharmacy/behavioral health/employee assistance, health care reimbursement account, dependent care assistance plan, short-term disability and long-term disability insurance, AD&D insurance, life insurance, 401(k), stock purchase plan to eligible employees. Costco is committed to a diverse and inclusive workplace. Costco is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to IT-Recruiting@costco.com If hired, you will be required to provide proof of authorization to work in the United States.