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About CFD Research: Since its inception in 1987, CFD Research has delivered innovative technology solutions within the Aerospace & Defense, Biomedical & Life Sciences, Intelligence & Sensing, and Energy & Materials industries. CFD Research has earned multiple national awards for successful application and commercialization of innovative component/system technology prototypes, multi-physics simulation software, multi-disciplinary analyses, and expert support services. Based in Huntsville, Alabama where laboratory facilities and headquarters are located, CFD Research also has office and laboratory facilities in Dayton, Ohio, prototyping test and evaluation facilities in Hollywood, Alabama, and office facilities in Fort Walton Beach, Florida. CFD Research is an ISO9001:AS9100D registered company and is appraised at CMMI Level II for Services. CFD Research is a 100% ESOP (employee-owned company) recognized in Inc. Magazine's Inc5000 as a top growing company for four of the last five years. Learn more at www.cfd-research.com CFD Research is seeking an AI/ML Engineer to build and deploy advanced artificial intelligence and machine learning solutions that l modernize mission systems and accelerate decision-making across the national security ecosystem. The candidate l| will contribute end-to-end—spanning data processing, model development, MLOps, and integration of scalable AI capabilities into operational environments. The work will leverage experience with ML-based NLP, LLMs and generative AI, computer vision, and modern software engineering practices. We value first-principles reasoning and physically interpretable models, so an interest in or experience developing hybrid systems is highly desirable. Candidates should be motivated by building systems that are scientifically explainable, empirically validated, and capable of operating robustly across sensing environments. You will partner with cross-functional engineering, mission SMEs, and product teams to deliver production-grade systems. Develop and implement AI/ML models—including NLP, LLM-based pipelines, deep learning architectures, and computer vision models—aligned to mission requirements. Build and maintain scalable data pipelines to support training, evaluation, and continuous improvement of models. Develop components of end-to-end production systems including microservices, APIs, automation frameworks, and cloud-native AI services. Integrate AI/ML capabilities into operational environments with attention to security, reliability, observability, and performance. Conduct model optimization, tuning, versioning, and A/B testing to ensure robust mission impact. Apply modern software engineering patterns (Python, Java, Scala, Rust; microservices; distributed systems). Collaborate with multi-disciplinary teams to identify mission needs and translate requirements into technical solutions. Prepare technical documentation, contribute to design reviews, and support accreditation processes in classified environments. Basic Qualifications 2–6 years of experience developing machine learning models (such as: NLP/LLM, CV, deep learning, generative AI, or related). 2–6 years of experience developing AI/ML capabilities to operate in a microservice stack. Candidate must possess an ACTIVE TS/SCI security clearance to be considered. Experience working with APIs, microservices, or distributed systems. Experience with data processing frameworks and scientific computing libraries (such as: NumPy, Pandas, PyTorch, TensorFlow, or scikit-learn). Experience configuring or deploying software systems in operational environments. Experience with CI/CD tooling, source control (such as GitLab), and containerization technologies (such as: Docker or Kubernetes). Bachelor's degree in a related STEM field. U.S. Citizenship is REQUIRED. Desired Qualifications Exposure to GPU programming (CUDA or RAPIDs) or AWS containerization. Understanding of LLM orchestration, RAG pipelines, or hallucination mitigation workflows. Familiarity with MLOps platforms or hybrid cloud environments (AWS, Azure, GCP). Familiarity with automated testing tools and model evaluation frameworks. Master's degree in Computer Science, AI/ML Engineering, Data Science, or related STEM field. TS/SCI active, willingness to take a polygraph Location: This role is based in the Dayton, OH area , and is 100% onsite. Benefits: CFD Research offers competitive salaries and excellent employee benefits, including an employer matching 401(k) and Employee Stock Ownership Plan (ESOP). CFD Research offers our Full-Time, permanent employee-owners a highly competitive insurance package, including medical, vision, and dental insurance. Additionally, we offer company paid leave, compensation time, parental leave, long-term and short-term disability, accidental death and dismemberment, and life insurance. Part-Time and Temporary employee-owners may receive partial or reduced benefits and leave time based on their employment status level. Performance appraisals occur twice a year and annual pay increases are based upon corporate goals, personal development, performance, and outstanding achievements. In addition, group and individual bonuses are awarded for exceptional performance. CFD Research is an EO employer - Veterans/Disabled and other protected categories

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services. Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We're deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront. We're looking for a Machine Learning Engineer to join Snap Inc! What you'll do: Build and deploy machine learning models that power core products, serving millions of Snapchatters Apply modern ML techniques to solve large-scale, real-world problems Own the full ML lifecycle from data analysis to production deployment Partner with cross-functional teams to prototype and launch ML-driven features Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production Knowledge, Skills & Abilities: Strong understanding of machine learning approaches and algorithms Able to prioritize duties and work well on your own Ability to work with both internal and external partners Skilled at solving open ambiguous problems Strong collaboration and mentorship skills Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices Minimum Qualifications: Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience 5+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 4+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years of post-grad machine learning experience Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning Preferred Qualifications: Advanced degree in computer science or related field Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks Experience working with machine learning, ranking infrastructures, and system design "Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a "default together" approach and expect our team members to work in an office 4+ days per week. At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable). Our Benefits: Snap Inc. is its own community, so we've got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap's long-term success! Compensation In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future. Zone A (CA, WA, NYC): The base salary range for this position is $209,000-$313,000 annually. Zone B: The base salary range for this position is $199,000-$297,000 annually. Zone C: The base salary range for this position is $178,000-$266,000 annually. This position is eligible for equity in the form of RSUs. If you believe this job description is missing required pay transparency information, please submit a report through this form: Job Description Pay Range Disclosure .

Archer is collaborating with J.P. Morgan to connect them with exceptional professionals for this role. Job Description We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. We are building a next generation, AI-driven Global Financial Crimes Strategic Monitoring solutions that detects AML risk, regulatory violations, transactions risk, misconduct, and behavioral anomalies. As a Senior MLE on the team, you will design, build and productionize Risk typologies/ features, data pipelines, supervised and unsupervised ML models, and LLM risk explainability that operate at scale across high-volume banking transactions. You will work at the intersection of Risk modeling, and NLP architectures, inference systems, regulatory explainability and auditability. This is a hands-on senior role requiring deep expertise in ML operations, LLM integration, scalable ML systems and production grade engineering discipline. This role offers a chance to collaborate with product managers, architects, data science and operational teams, while also engaging in software engineering communities to explore new and emerging technologies. Job Responsibilities Design, build, collaborate, and operate ML models Design, build and operate LLM solutions Design and build feedback and accuracy measurement techniques for AI solutions Design, build, and operate risk features data pipelines in Databricks Conduct monitoring to detect and alert drift, bias and performance degradation Work closely within a cross-functional team following agile based processes Collaborate closely with Product Managers, SRE and Compliance SMEs to continuously improve product adoption, reliability and outcomes Required Qualifications, Capabilities, And Skills PhD in Computer Science, Data Science, AI or similar fields with with 2+ years of experience Or MS in Computer Science, Data Science, AI or similar fields with with 4+ years of experience or BS in Computer Science, Data Science, AI or similar fields with with 8+ years of experience Strong foundation in Information Retrieval, Natural Language Processing and Expert in functional programming and JVM based languages- Python, Java Experience integrating models into cloud scale, microservices based architectures Experience with one or more ML frameworks - Pytorch, Tensorflow, SciKit, NeMo, Huggingface Transformers Hands-on experience with AWS services, and Databricks Experience/Exposure to SQL, NoSQL and messaging stacks Excellent verbal & written communication skills and bias for action and ownership in early stage env Operational experience in supporting an enterprise grade ML application in production Preferred Qualifications, Capabilities, And Skills Knowledge of Firm Databricks CDAO platform is good to have Experience with building production-grade ML pipelines, APIs and MLOps frameworks Experience in AML, monitoring and investigations systems is a strong plus Good understanding of data engineering concepts, distributed systems, and scalable architectures Familiarity with vector databases, model serving, and inference optimization is a plus ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans About The Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

About The Role The role owns building, training, and deploying machine learning models that run in production — not prototypes that die in a notebook. The team ships models that serve real traffic daily, where accuracy, latency, and cost all matter. This is a hands-on engineering role: designing training pipelines, optimizing inference, and building the MLOps infrastructure that keeps models healthy at scale. The role reports into an applied ML org and works directly with data engineers, backend teams, and product stakeholders. Key Responsibilities Design, train, and productionize ML models (classification, ranking, NLP, and LLM-based systems) using PyTorch or TensorFlow Build and maintain scalable data and feature pipelines in Python and PySpark, ensuring consistency between training and serving environments Deploy and version models on AWS or GCP using SageMaker, Vertex AI, or Kubernetes-based serving stacks (TorchServe, Triton, KServe) Optimize model inference for latency and cost: quantization, distillation, batching, and GPU utilization tuning Instrument model monitoring for data drift, performance regression, and automated retraining triggers using tools like Evidently or custom pipelines Run rigorous offline and online experiments (A/B tests, shadow deployments) and communicate results clearly to technical and non-technical stakeholders Contribute to ML platform improvements: CI/CD for models, experiment tracking (MLflow, W&B), and shared evaluation frameworks What We Are Looking For 3–7 years of experience in machine learning engineering or applied ML, including multiple models shipped to production Expert-level Python and hands-on depth with PyTorch or TensorFlow; strong software engineering fundamentals (testing, code review, system design) Production experience with cloud ML infrastructure: AWS (SageMaker, ECS/EKS) or GCP (Vertex AI, GKE) Solid grasp of ML fundamentals: evaluation metrics, regularization, class imbalance, and the gap between offline metrics and real-world performance Experience with MLOps tooling: Docker, Kubernetes, CI/CD pipelines, and experiment tracking systems BS in Computer Science, Statistics, Engineering, or equivalent practical experience; MS a plus Bonus: experience fine-tuning or serving LLMs, GPU optimization (CUDA, TensorRT), Rust/Go for inference services, or contributions to open-source ML projects

Job Description A fast-growing technology company is seeking a Senior Machine Learning Engineer to join its team in the Greater Boston area. This is a hybrid opportunity that combines cutting-edge machine learning development with the chance to influence the direction of AI-driven products and platforms. In this role, you will design, develop, deploy, and optimize machine learning models that drive business-critical applications. You will work closely with data scientists, software engineers, product managers, and leadership to transform complex data into scalable solutions. The ideal candidate is passionate about applying advanced machine learning techniques in production environments and has a strong track record of delivering measurable results. This position offers the opportunity to work on challenging problems involving predictive modeling, deep learning, large-scale data processing, and MLOps within a collaborative and innovative environment. Required Skills & Experience 7+ years of professional experience in Machine Learning, Data Science, or Software Engineering Strong experience building and deploying machine learning models in production environments Proficiency with Python and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform Deep understanding of statistics, machine learning algorithms, model evaluation, and experimentation Experience with data engineering tools and distributed computing frameworks Strong software engineering fundamentals, including version control, testing, and CI/CD Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field Desired Skills & Experience Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field Experience with large language models (LLMs), generative AI, or NLP applications Familiarity with Kubernetes, Docker, and MLOps best practices Experience building recommendation systems, forecasting models, or computer vision applications Exposure to real-time machine learning systems and large-scale data pipelines Prior leadership or mentoring experience What You Will Be Doing Daily Responsibilities 80% Hands On Design and develop machine learning models and AI-driven solutions Build scalable training, deployment, and monitoring pipelines Collaborate with product and engineering teams to translate business requirements into technical solutions Optimize model performance, reliability, and scalability Conduct experimentation, model validation, and performance analysis Establish best practices for machine learning engineering and MLOps Mentor junior engineers and contribute to technical leadership initiatives Stay current with emerging machine learning and AI technologies The Offer Base Salary: $220,000 - $240,000 per year Performance-based annual bonus Equity or long-term incentive package Hybrid work schedule (3 days onsite) in the Boston, MA area You will receive the following benefits Medical Insurance Dental Benefits Vision Benefits Paid Time Off (PTO) 401(k) with company match Flexible work arrangements Professional development and continuing education support Applicants must be currently authorized to work in the US on a full-time basis now and in the future. Posted By: Nick Ramler

Description We are seeking a talented Data Engineer to join our EC2 + EBS + Networking Product BI team. You will own end-to-end analytics for one or more Compute service areas — building and monitoring ETL pipelines, delivering executive reports, creating metrics and callouts on service performance, and producing deep-dive analyses that shape product roadmaps for services used by millions of AWS customers worldwide. Key job responsibilities ETL Monitoring & Pipeline Operations: Own the reliability and timeliness of 200+ data pipelines serving executive-facing reports. Today, the team uses automated alarms for real-time monitoring and AI-powered agents that self-heal failures and triage tasks — you will maintain and extend this system using Redshift, orchestration frameworks, and AWS data services. Report Delivery & Business Reviews: Own and operate Weekly/Daily Business Review (WBR/DBR) reporting for EC2 services, ensuring accurate, timely delivery to CEO/S-Team and VP-level stakeholders. Today, report generation, validation, and delivery are automated via LLMs — you will operate and improve these workflows. Callout Generation: Generate callouts on service performance — identifying week-over-week trends, anomalies, and key drivers to surface in executive reviews. Today, callout generation across all 9 services is LLM-automated — you will own the quality bar and continuously improve prompt and pipeline accuracy. Data Ingestion & Metric Creation: Ingest new data sources and build metrics that track business health (usage, capacity, adoption, customer growth). Today, the team maintains scalable ETL pipelines in Redshift with workflow orchestration — you will ensure metrics remain sustainable, reproducible, and available on demand. Analysis & Deep Dives: Conduct deep-dive analyses for Product Managers, Sales, and Finance teams. Today, the team uses a proprietary analytics platform with governed SOPs, stored context, and pre-built queries — enabling any stakeholder to deep-dive with technical depth and reproducibility. You will author and maintain these SOPs and analyses. Dashboard Development: Design, build, and maintain interactive dashboards (QuickSight, Weave) covering product trends, customer growth, instance utilization, and feature adoption. Today, dashboards serve 100+ Product Managers across 11 engagement areas — you will own dashboards for your service areas and improve self-serve capabilities. Stakeholder Partnership: Work closely with Product Managers, service finance teams, and cross-functional partners to translate business questions into data products and present findings to senior leaders. Today, the team partners across EC2, Networking, and Compute product families — you will be the primary analytics point of contact for your assigned service areas. About The Team We are the EC2 + Networking Product BI team within AWS Analytics & Engineering (AAE). We serve as the data and analytics partner for Amazon Elastic Compute Cloud (EC2), Networking Services, and adjacent Compute product families — supporting 100+ Product Managers across 11 engagement areas. Our Core Work Includes ETL Pipeline Monitoring & Operations: We build and operate 200+ data pipelines that ingest, transform, and serve petabyte-scale datasets across EC2, Networking, and Compute services. Reliability and timeliness are critical — our reports feed directly into CEO/S-Team weekly reviews. We use automated alarms for real-time pipeline monitoring and AI-powered agents to self-heal failures and triage tasks, minimizing manual intervention at this scale. Report Delivery & Callout Generation: We deliver Weekly and Daily Business Review (WBR/DBR) reports across 9 Compute services (EC2 Core, Gen AI, EBS, Bedrock, SageMaker, ECS, EKS, ECR, Lambda), generating callouts on service performance that inform executive decision-making. Report generation, validation, and callout generation are all done via LLMs — enabling consistent quality, accuracy, and speed at scale. Data Ingestion & Metric Creation: We design and maintain metrics that track business health — usage, capacity, adoption, customer growth — ensuring they are sustainable, reproducible, and available on demand. Analysis & Deep Dives: We produce analyses for Product Managers, Sales, and Finance teams using our proprietary analytics platform where governed SOPs, context, and prior work live. These SOPs help all PMs, Sales, and Finance stakeholders deep-dive with governed data, technical depth, and the right queries — enabling reproducibility and easy follow-ups across the organization. Everything we build is designed to be sustainable, reproducible, and available on demand — so any team member can pick up, extend, or re-run work without starting from scratch. Basic Qualifications 3+ years of data engineering experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience 3+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience 3+ years of in the job offered or a related occupation experience 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field Experience with data modeling, warehousing and building ETL pipelines Preferred Qualifications Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases) 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 - 132,100.00 - 178,800.00 USD annually Company Amazon Development Center U.S., Inc. Job ID: A10591361

Description We are looking for a Senior Business Intelligence Engineer (BIE) to drive the use of AI in analytics with high exposure to executive level business decision making support. In this role you will define and implement scalable processes, diving deep into the product and program metrics globally across multiple business units. You will apply both business and technical acumen in a fast-paced, ambiguous and innovative environment. Key job responsibilities Design and build AI tools that derive actionable insights from some of the world's largest datasets Own the design and development of automated solutions for recurrent reporting and in-depth analyses including learning, publishing, and managing our operational business metrics decks Drive continuous improvement of our analytical processes by automating, scaling, and simplifying self-service support for our customers Invent new ways to explore our data and work with Product Managers to identify opportunities and transform business problems into defined data and reporting requirements Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation A day in the life Your day will be a blend of technical investigation and collaborative problem-solving. You'll dive deep into the problems our stakeholders are facing, and design tech solutions to solve them. You will teach your teammates how to better use the latest technologies such as AI, both in their internal processes and outwardly with their stakeholder-facing products. When stakeholders come to you with problems, you will be expected to find a sustainable solution that prevents the problems from surfacing again. You will turn complex input metrics into actionable insights that drive high-impact business outcomes. Expect to engage in cross-functional discussions, influence executive leadership, and develop strategies to enhance org-wide AI effectiveness. About The Team We are a collaborative group of technology and business experts dedicated to pushing the boundaries of AI performance optimization. Our team thrives on innovation, continuous learning, and creating transformative solutions that make a tangible impact across various business domains. We value diverse perspectives and empower team members to contribute unique insights that drive our collective success. Basic Qualifications 5+ years of as a Data Analyst, Data Engineer, Business Intelligence Analyst, or a related occupation experience Experience creating AI-based tools that are used by non-technical stakeholders at an executive level Experience managing, analyzing and communicating results to executive leadership Experience processing large, multi-dimensional datasets from multiple sources Experience in the data/BI space Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field Preferred Qualifications Experience working directly with business stakeholders to translate between data and business needs Experience with AWS technologies Experience using Cloud Storage and Computing technologies such as AWS Redshift, S3, Hadoop, etc. Experience in scripting for automation (e.g. Python) and advanced SQL skills. Master's degree in statistics, data science, or an equivalent quantitative field Experience developing automated reporting Statistical analysis experience Experience programming to extract, transform and clean large (multi-TB) data sets 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, AZ, Tempe - 130,400.00 - 176,300.00 USD annually USA, TN, Nashville - 123,800.00 - 167,500.00 USD annually USA, TX, Austin - 130,400.00 - 176,300.00 USD annually USA, VA, Arlington - 130,400.00 - 176,300.00 USD annually USA, WA, Bellevue - 130,400.00 - 176,300.00 USD annually Company Amazon.com Services LLC Job ID: A10592915

Let's face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship. We do. We can't cram it all in here, but you'll start noticing it from the first interview. Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you've ever met (yes, each with their own personal BetterUp Coach), and most importantly, work that matters. This makes for a remarkably focused and fulfilling work experience. Frankly, it's not for everyone. But for people with fire in their belly, it's a game-changing, career-defining, soul-lifting move. Join us and we promise you the most intense and fulfilling years of your career, doing life-changing work in a fun, inventive, soulful culture. If that sounds exciting—and the job description below feels like a fit—we really should start talking. We are a hybrid company with a focus on in-person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include: Austin, TX; New York City, NY; San Francisco, CA; and the Washington, DC metro area. Please ensure you can realistically commit to this structure before applying. The Opportunity BetterUp is looking for a Senior Analytics Engineer with experience building data modeling systems within a modern data stack, supported by intelligent data warehousing and adaptable business intelligence systems, to join our team. At BetterUp we believe data is critical to our success and this role on the Analytics Engineering team will be crucial to this strategy of delivering exceptional data products that will drive key business decisions. If you are passionate about helping people reach their potential, thrive in a fast-paced startup environment where you get to build the future, and love data then this is the role for you. What You'll Do Architect, build and maintain efficient and reliable data products (dbt models, pipelines, Looker explores, visualizations, etc.) that enable data driven decision making. Build and maintain ELT pipelines from source systems to data warehouses. Influence strategy and drive execution of our analytical roadmap delivering self-service business intelligence at scale. Provide leadership and mentorship to other engineers fostering collaboration, knowledge sharing and a high bar for quality. Improve end users trust and confidence by driving best practices with regards to data discoverability, observability, lineage and stewardship. Contribute towards a robust data security strategy protecting sensitive information and content. Solve critical business problems through the application of programming, optimization, automation, and analytical skills. If you have some or all of the following, please apply: Minimum 5+ years of relevant experience in data engineering and/or analytics engineering Advanced SQL skills with 5+ years of deep experience with Snowflake or similar DB Expertise with data modeling and ETL/ELT (dbt preferred, pipeline development a plus) Seasoned developer (5+ years) within a modern business intelligence tool (Looker preferred) Experience applying software engineering principles (testing, version control, code reviews, CI/CD, etc.) in your working process, to scale analytical development Proven track record of working with data teams in a fast-paced, startup environment Proven track record of successfully working cross-functionally with both technical and non-technical stakeholders Solutions-driven and thrives when given ambiguous, open-ended problems Proven success driving projects through implementation to completion, including stakeholder education and onboarding Obsessed with data protections and privacy (i.e. PII, GDPR, FedRAMP, FIPS, etc.) Hands-on experience using AI tools in your development workflow (e.g., Claude Code, Cursor, AI-assisted dbt and SQL development) AI at BetterUp Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We're looking for teammates who are excited to evolve alongside technology – people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation. During our interview process, you'll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact. As a Senior Analytics Engineer, You'll Architect domain-level AI reinvention: identify the highest-leverage AI opportunities in how we build and scale our data products, secure the resources to test them, and install repeatable mechanisms that lock in proven gains across several teams Build scalable AI-powered systems, such as intelligent pipeline monitoring, automated data quality checks, and AI-assisted development, that change how analytical work gets done across multiple teams Establish governance frameworks and best practices for responsible AI usage at scale within the analytics function We encourage all candidates to share examples of how they've used AI tools in their work—whether it's AI-assisted SQL generation, LLM-powered data documentation, automated anomaly detection, or other applications. We view AI fluency as a complement to craft, not a replacement for it. Benefits At BetterUp, we are committed to living out our mission every day and that starts with providing benefits that allow our employees to care for themselves, support their families, and give back to their community. Access to BetterUp coaching; one for you and one for a friend or family member A competitive compensation plan with opportunity for advancement Medical, dental, and vision insurance Flexible paid time off Per year: All federal/statutory holidays observed 4 BetterUp Inner Workdays (https://www.betterup.co/inner-work) 5 Volunteer Days to give back Learning and Development stipend Company wide Summer & Winter breaks Year-round charitable contribution of your choice on behalf of BetterUp 401(k) self contribution We are dedicated to building diverse teams that fuel an authentic workplace and sense of belonging for each and every employee. We know applying for a job can be intimidating, please don't hesitate to reach out — we encourage everyone interested in joining us to apply. BetterUp Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, disability, genetics, gender, sexual orientation, age, marital status, veteran status. In addition to federal law requirements, BetterUp Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. At BetterUp, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, residence location, as well as market indicators. The range below is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future. The base salary range for this role is as follows: $175,000 – $220,000: New York City and San Francisco $158,000 – $198,000: All other locations We value your privacy. Your personal data will be processed in accordance with our Privacy Policy . If you have any questions about the privacy of your personal data or your rights with regards to your personal data, please reach out to support@betterup.co

Brief Description YOUR ROLE We're seeking a Senior Analytics Engineer to help shape the future of data-driven decision making at our rapidly growing, insurance technology company. As a key member of our data team, you'll architect and implement analytics solutions that power both strategic insights and operational workflows. You'll work at the intersection of our modern data stack and business operations — building robust data models, designing self-service data applications, and leading the migration from our legacy Redshift and Tableau environment to our modern stack. This role offers a unique opportunity to work with cutting-edge tools (dbt, Snowflake, Sigma, Hex, Claude) while having significant influence on our data strategy and technical architecture. You'll collaborate closely with business teams to transform complex data into actionable insights, self-service analytics, and AI-powered applications. What You'll Do Design, build, and maintain data models using dbt core, ensuring efficient, scalable, and well-documented analytics solutions Lead and execute the migration of data assets from Redshift and Tableau to our modern stack — Snowflake, Sigma, and Hex — ensuring data quality and business continuity throughout Build interactive data applications, dashboards, and reports in Sigma and Hex that enable self-service analytics for business stakeholders Design, build, and govern our centralized semantic layer to standardize business metrics and enable true self-service analytics across Sigma and Hex Develop and maintain Python scripts for analytics automation, predictive models, and operational reporting Implement and maintain data quality testing frameworks to ensure reliable, trustworthy data Integrate AI and LLM capabilities (including Claude) into analytics workflows to automate data enrichment, text analysis, and predictive modeling for insurance use cases Create and manage JIRA epics, stories, and tasks to track development work Collaborate with stakeholders to understand business requirements and translate them into technical solutions Additional duties and responsibilities as assigned. Requirements YOUR LOCATION This is a fully remote role, with the exception of onboarding and optional in-office events. Skills & Experience 5+ years of experience in analytics engineering or a similar technical role Expert-level SQL skills with deep understanding of data warehouse concepts Hands-on experience with dbt for data transformation and modeling — dbt core experience preferred Proficiency building data applications, dashboards, and reports in Sigma and/or Hex Proven experience leading or executing a migration from a legacy data warehouse (Redshift) or BI tool (Tableau) to a modern analytics stack Expert-level experience with Snowflake as a cloud data warehouse (required); familiarity with AWS Redshift a plus for migration context Proven experience building and maintaining a semantic layer / metrics catalog to serve multiple downstream applications Working knowledge of Python for analytics automation, predictive modeling, and reporting Experience with version control systems (Git) and CI/CD practices Practical experience leveraging AI/LLMs within a data stack to solve business problems — including prompt engineering, AI-assisted analytics, or GenAI tools in Hex, Sigma or Snowflake Experience with data lakehouse technologies, including Apache Iceberg and AWS Glue (a plus) Experience in commercial insurance, financial services, or venture-backed technology companies Track record of building data solutions in B2B SaaS or enterprise software companies Experience using JIRA for project management and tracking Excellent communication skills with high attention to detail Bachelor's degree in Computer Science, Engineering, Mathematics, or related field Self-starter who thrives in a fast-paced environment, capable of juggling multiple initiatives and meeting strict deadlines Physical Requirements Must be able to sit/stand/walk for prolonged periods of time (up to 8 hours per day), at a desk working on a computer. Must be able to use standard office equipment for extended periods of time, including but not limited to, a mouse, keyboard, phone and video conferencing. Summary Bold Penguin is the premier digital broker for commercial insurance. Their technology expands top-of-funnel demand and increases yield for enterprise partners. Through digital distribution, wholesale capabilities, and AI-driven insights, they transform the lifecycle of both simple and complex risks, from prospecting to placement. Benefits We offer competitive compensation and progressive benefits that include: Medical, Dental, and Vision Flexible PTO Policy 401(k) with a company match Employee Assistance Program Parental Leave Disability and Life Benefits Stay connected to the Glacier. We have great SLACK channels for work and play. We also like to video conference and hold all-hands "Waddles" regularly. Penguin bling. Like swag themed after a certain Antarctic bird? Just. You. Wait. Bold Penguin believes in inclusion. That's why we're proud to be an equal opportunity employer that considers all qualified applicants regardless of race, color, religion, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. To learn more about our results-focused culture and employee-focused perks, read more on our careers page .

Let's face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship. We do. We can't cram it all in here, but you'll start noticing it from the first interview. Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you've ever met (yes, each with their own personal BetterUp Coach), and most importantly, work that matters. This makes for a remarkably focused and fulfilling work experience. Frankly, it's not for everyone. But for people with fire in their belly, it's a game-changing, career-defining, soul-lifting move. Join us and we promise you the most intense and fulfilling years of your career, doing life-changing work in a fun, inventive, soulful culture. If that sounds exciting—and the job description below feels like a fit—we really should start talking. We are a hybrid company with a focus on in-person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include: Austin, TX; New York City, NY; San Francisco, CA; and the Washington, DC metro area. Please ensure you can realistically commit to this structure before applying. The Opportunity BetterUp is looking for a Senior Analytics Engineer with experience building data modeling systems within a modern data stack, supported by intelligent data warehousing and adaptable business intelligence systems, to join our team. At BetterUp we believe data is critical to our success and this role on the Analytics Engineering team will be crucial to this strategy of delivering exceptional data products that will drive key business decisions. If you are passionate about helping people reach their potential, thrive in a fast-paced startup environment where you get to build the future, and love data then this is the role for you. What You'll Do Architect, build and maintain efficient and reliable data products (dbt models, pipelines, Looker explores, visualizations, etc.) that enable data driven decision making. Build and maintain ELT pipelines from source systems to data warehouses. Influence strategy and drive execution of our analytical roadmap delivering self-service business intelligence at scale. Provide leadership and mentorship to other engineers fostering collaboration, knowledge sharing and a high bar for quality. Improve end users trust and confidence by driving best practices with regards to data discoverability, observability, lineage and stewardship. Contribute towards a robust data security strategy protecting sensitive information and content. Solve critical business problems through the application of programming, optimization, automation, and analytical skills. If you have some or all of the following, please apply: Minimum 5+ years of relevant experience in data engineering and/or analytics engineering Advanced SQL skills with 5+ years of deep experience with Snowflake or similar DB Expertise with data modeling and ETL/ELT (dbt preferred, pipeline development a plus) Seasoned developer (5+ years) within a modern business intelligence tool (Looker preferred) Experience applying software engineering principles (testing, version control, code reviews, CI/CD, etc.) in your working process, to scale analytical development Proven track record of working with data teams in a fast-paced, startup environment Proven track record of successfully working cross-functionally with both technical and non-technical stakeholders Solutions-driven and thrives when given ambiguous, open-ended problems Proven success driving projects through implementation to completion, including stakeholder education and onboarding Obsessed with data protections and privacy (i.e. PII, GDPR, FedRAMP, FIPS, etc.) Hands-on experience using AI tools in your development workflow (e.g., Claude Code, Cursor, AI-assisted dbt and SQL development) AI at BetterUp Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We're looking for teammates who are excited to evolve alongside technology – people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation. During our interview process, you'll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact. As a Senior Analytics Engineer, You'll Architect domain-level AI reinvention: identify the highest-leverage AI opportunities in how we build and scale our data products, secure the resources to test them, and install repeatable mechanisms that lock in proven gains across several teams Build scalable AI-powered systems, such as intelligent pipeline monitoring, automated data quality checks, and AI-assisted development, that change how analytical work gets done across multiple teams Establish governance frameworks and best practices for responsible AI usage at scale within the analytics function We encourage all candidates to share examples of how they've used AI tools in their work—whether it's AI-assisted SQL generation, LLM-powered data documentation, automated anomaly detection, or other applications. We view AI fluency as a complement to craft, not a replacement for it. Benefits At BetterUp, we are committed to living out our mission every day and that starts with providing benefits that allow our employees to care for themselves, support their families, and give back to their community. Access to BetterUp coaching; one for you and one for a friend or family member A competitive compensation plan with opportunity for advancement Medical, dental, and vision insurance Flexible paid time off Per year: All federal/statutory holidays observed 4 BetterUp Inner Workdays (https://www.betterup.co/inner-work) 5 Volunteer Days to give back Learning and Development stipend Company wide Summer & Winter breaks Year-round charitable contribution of your choice on behalf of BetterUp 401(k) self contribution We are dedicated to building diverse teams that fuel an authentic workplace and sense of belonging for each and every employee. We know applying for a job can be intimidating, please don't hesitate to reach out — we encourage everyone interested in joining us to apply. BetterUp Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, disability, genetics, gender, sexual orientation, age, marital status, veteran status. In addition to federal law requirements, BetterUp Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. At BetterUp, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, residence location, as well as market indicators. The range below is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future. The base salary range for this role is as follows: $175,000 – $220,000: New York City and San Francisco $158,000 – $198,000: All other locations We value your privacy. Your personal data will be processed in accordance with our Privacy Policy . If you have any questions about the privacy of your personal data or your rights with regards to your personal data, please reach out to support@betterup.co

Socomec Group (Socomec) is a global leader in electrical equipment engineering and manufacturing, specialized in low voltage energy performance. Socomec North America (NAM) is Socomec?s organization overseeing all operations in North America. We are seeking a Mechanical Engineer within the Engineering/Product Development Team is focused on electromechanical design and packaging for the company?s product lines (Power Conversion, Energy Storage, Power System Monitoring, etc.), research & development, process and product optimization-improvement among others. This position provides individual contributor within Mechanical Engineering. Responsible to observe and implement technical governance, design standards, engineering methodology, technical reviews, use of technology and engineering procedures. Key Responsibilities And Accountabilities Design of metal cabinetry and mechanical systems integration using SolidWorks 3-D modeling. Electro-mechanical design and packaging of electro-magnetic components incorporating a number of associated power assemblies work as a system using SolidWorks 3-D modelling. Sourcing and parametric modeling of electro-mechanical/magnetic library components. Prepare detailed manufacturing data packages including 2D and MBD drawings, including the complete product configurations with detailed BOM structures in ERP system. Support of factory floor activities in troubleshooting, assembly and retrofit, including Support of general manufacturing activities as may be required or designated. Documentation of all manufacturing package according to the established company procedures, standard of works, practices and product line. Other activities that relate to product development and order fulfilment, including mechanical design to assigned target requirements, DFM and DFA considering cost and throughput. Prepare technical or cost reports to propose or assess decisions or planning of related projects and activities. Essential Qualifications, Experience, And Skills Bachelor's degree in Mechanical / Electro-Mechanical Engineering. 3-5 years of experience in Mechanical Engineering / Manufacturing, both technical and hands-on Demonstrated experience and knowledge in electrical enclosure packaging for electrical power components in indoor and outdoor environments. Ability to learn new skill sets with respect to supporting existing and future Socomec products. Thrives in a fast-paced innovative environment where several interdependent technologies and products are being developed simultaneously. Adaptable to rapid changes in priority planning keeping visible accountability. Demonstrates initiative and a passion for achieving results. Strong analytic problem-solving capabilities. Resourceful, innovative, and energetic. Strong collaboration and teamwork skills. Must be legally authorized to work in Canada without company sponsorship. Proficient in SolidWorks (preferred) CAD systems, with strong emphasis on Sheetmetal, Drawings, PDM and large assembly modules. Preferred knowledge and hands on practical experience in Configure to order products and BOM management, Static Stress FEA and SolidWorks DriveWorks automation tool or similar. Able to prepare professional documentation of manufacturing package, drawings, etc. Strong organizational skills, Capable to execute projects with proper tracking, visibility and ownership, driving them proactively to closure from end to finish. Strong verbal and written communication skills. Additional Requirements This role is located in an office and remote environment (at management?s discretion), with regular visits to the manufacturing, test bay and assembly environment. Must be available for possible business travel to locations in Canada, USA and Europe. Must possess and maintain a valid passport for international travel. Commitment to Health and Safety best practice and regulations. Adherence to company policies. Team Si

Department: Data Location: Remote Description Grasshopper Bank is a client-first , digital bank built for the business and innovation economy, with an obsession for providing leading-edge technology, solutions-driven products and superior service through a combination of passionate people and digital resources. We are a highly experienced team who pride ourselves on diversity of thought and perspective . Nationally chartered, our portfolio of products and services range from VC, PE & Portfolio Companies to SBA Lending, as well as direct SMB and Embedded Banking. Our entrepreneurial drive allows us to support the growth and success of a wide range of clients at every stage of their business through inclusive partnership . We seek out team members who will enable both our organization and our people to grow and thrive through collaboration and acting with integrity and respect. Our focus on cross-functional teamwork provides a culture where ideas are valued, accountability is encouraged , and successes are celebrated . We welcome all those searching for the opportunity to contribute to banking innovation that influences and supports the emerging digital world of Financial Services. Our digital first approach enables our teams the flexibility to work remotely. We have offices in NYC and Boston. What You'll Do As a Customer Analytics Engineer , you will operate at the intersection of modern data engineering, customer behavior analytics, and growth enablement. Reporting to the Director of BI & Analytics, you will serve as the technical engine and strategic architect behind our bank-wide Customer 360 and customer lifecycle analytics initiatives. In this high-impact role, you will move beyond standard descriptive reporting to build the foundational data models, pipelines, and semantic layers that explain who our clients are, how they interact with our digital banking platforms, and what drives long-term customer lifetime value (LTV). You will be responsible for modeling complex customer event streams, digital touchpoints, and transaction histories into analytics-ready models in Google BigQuery, powering executive Tableau reporting and directly activating customer data downstream into marketing and engagement engines (such as Braze). If you love writing clean, performant SQL/Python transformation logic, unraveling complex customer journeys, and partnering with Product and Marketing leaders to unlock top-line revenue, this role is for you. Customer 360 & C-MDM Modeling: Design, build, and optimize scalable dimensional models (Kimball methodology) and One Big Table (OBT) datasets in Google BigQuery that unify core banking records, digital session logs, and touchpoints into a trusted, bank-wide customer master (C-MDM) and single source of truth. Identity Resolution, Governance & Attribution: Establish robust customer identity mapping and multi-touch marketing attribution models across diverse platforms, while championing master data management (C-MDM) principles, data quality, and governance across all customer data pipelines. Semantic Layer & Master Data Development: Formalize bank-wide customer entities, core segmentations, and Critical Data Elements (CDEs)—such as Active User definitions (DAU/MAU), primary operating account status, feature adoption, and dormancy thresholds—to align business and technical definitions under a unified C-MDM framework. Scalable ELT Pipelines: Design, deploy, and maintain resilient ELT/ETL pipelines (using SQL, Python, and orchestration tools) to ingest, clean, and enrich raw customer interaction data, API payloads, and core snapshot tables. Downstream Marketing & Activation Sync: Engineer reliable pipelines and reverse-ETL workflows that sync enriched customer traits, behavioral events, and engagement tiers directly into marketing automation platforms (e.g., Braze) and CRM systems to power automated lifecycle campaigns. Data Quality & Observability: Implement automated testing, anomaly detection, and schema validation across customer data pipelines to guarantee platform accuracy, uptime, and alerting. Customer Journey & Cohort Dashboards: Design and maintain intuitive, executive-ready Tableau dashboards focusing on customer acquisition funnels, retention curves, product penetration, churn indicators, and deposit velocity. Storytelling with Data: Translate complex, multi-layered data into clear, actionable narratives that answer the "so what?" for business line leaders and product managers. Performance Optimization: Continuously monitor and tune BigQuery queries and Tableau extracts to ensure rapid workbook performance and cost-efficient query processing. Strategic Growth Partner: Collaborate closely with Marketing, Product, and Business Line leaders to translate business hypotheses into quantitative frameworks and tracking requirements. Data Stewardship & Literacy: Champion data governance best practices, document customer data lineages and KPI definitions in the Data Steward Playbook, and coach end-users on self-service data discovery. What You Need Experience: 2–4+ years of hands-on experience in a hybrid data role such as Analytics Engineer, Customer Data Engineer, BI Developer, or Marketing Data Engineer. Prior experience in fintech, commercial banking, or digital banking platforms is preferred. Advanced SQL & BigQuery: Expert-level SQL skills, including advanced analytical window functions, complex CTEs, array/struct unnesting, and performance tuning within cloud data warehouses (Google BigQuery strongly preferred). Dimensional & Event Data Modeling: Strong experience with dimensional modeling, star schemas, and structuring behavioral/event-based data models (hands-on experience with dbt for modeling transformations and lineage is a strong plus). Python & Pipeline Engineering: Demonstrated experience using Python for data transformation, API integrations, and workflow automation. Experience scheduling and orchestrating DAGs using tools like Apache Airflow or Google Cloud Composer is preferred. Tableau Expertise: Deep proficiency in Tableau Desktop and Tableau Server/Cloud, including Level of Detail (LOD) expressions, parameters, and thoughtful dashboard UX/UI design principles. Customer Analytics Acumen: Strong conceptual understanding of customer lifecycle metrics: Customer Acquisition Cost (CAC), Lifetime Value (LTV), cohort retention, and churn. Familiarity with reverse-ETL workflows or customer data activation is a plus. Communication & Collaboration: Proven track record of presenting complex data insights to non-technical stakeholders and driving cross-functional alignment. Education: Bachelor's degree in Computer Science, Information Systems, Data Analytics, Mathematics, Engineering, or equivalent practical experience.