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Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title Applied AI Engineer Location: 100% Remote (Continental United States) Position Type: Full-time, Direct W2 Salary Range: $130,000–$180,000 Annually (based on experience) Experience Required: 10+ Years Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. Job Summary Bright Vision Technologies is seeking a highly experienced Applied AI Engineer with 10+ years of experience in Artificial Intelligence, Machine Learning, and Deep Learning to design, develop, and deploy enterprise-scale AI solutions. The ideal candidate will possess deep expertise in Python, PyTorch or JAX, Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision, and MLOps , with a proven track record of taking AI models from research to production. This role requires strong technical leadership, hands-on development, and the ability to architect scalable, secure, and high-performance AI systems. Key Responsibilities Design, develop, and deploy production-grade AI and machine learning solutions that address complex business challenges. Architect scalable training, inference, and MLOps pipelines for enterprise AI applications. Develop, fine-tune, evaluate, and optimize Large Language Models (LLMs) , deep learning models, and multimodal AI systems. Build AI applications leveraging Retrieval-Augmented Generation (RAG) , vector databases, embeddings, prompt engineering, and agentic AI frameworks. Design and implement machine learning pipelines for NLP, Computer Vision, recommendation systems, and predictive analytics. Optimize model performance, latency, scalability, and infrastructure utilization across cloud and distributed computing environments. Collaborate with data scientists, software engineers, product managers, and business stakeholders to deliver production-ready AI solutions. Establish best practices for model evaluation, Responsible AI, governance, security, monitoring, and lifecycle management. Mentor junior AI engineers and contribute to technical leadership, architecture reviews, and engineering best practices. Evaluate emerging AI technologies, foundation models, and frameworks to drive continuous innovation. Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical discipline. 10+ years of professional experience in Artificial Intelligence, Machine Learning, Deep Learning, or Applied AI. Expert-level programming skills in Python with extensive experience using PyTorch, JAX, or TensorFlow . Proven experience developing and deploying Large Language Models (LLMs) , NLP, Computer Vision, and deep learning applications in production. Strong knowledge of distributed training, GPU optimization, model serving, and production ML deployment. Hands-on experience with MLOps , CI/CD pipelines, model monitoring, feature engineering, and automated ML workflows. Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) for AI workloads. Strong understanding of machine learning algorithms, statistics, model evaluation, experimentation, and optimization techniques. Excellent problem-solving, communication, collaboration, and technical leadership skills. Preferred Qualifications Experience with LLM fine-tuning , Retrieval-Augmented Generation (RAG) , agentic AI , multimodal AI , and vector databases such as Pinecone, Weaviate, Milvus, or FAISS . Hands-on experience with AI orchestration frameworks such as LangChain , LlamaIndex , LangGraph , or similar technologies. Experience deploying AI applications using Kubernetes, Docker, Ray, or distributed inference frameworks. Publications in AI/ML conferences, open-source contributions, patents, or recognized technical leadership in the AI community. Knowledge of Responsible AI, AI governance, model security, fairness, explainability, and regulatory compliance. Ph.D. or Master's degree with a specialization in Artificial Intelligence, Machine Learning, Computer Vision, or Natural Language Processing. Interested in this opportunity? Apply today for immediate consideration! Email your updated resume: jaya@bvteck.com Call or Text: (908) 505-3545 Learn More Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

Senior Machine Learning Engineer Remote | Direct Hire $160K – $175K Base We are seeking a hands-on Senior Machine Learning Engineer to architect, build, and own end-to-end production ML systems for a growing enterprise SaaS platform. This role focuses on developing intelligent systems that classify, normalize, and enrich large volumes of complex business and transactional data using machine learning, NLP, and modern AI technologies. Responsibilities Architect and develop end-to-end production ML systems. Build classification, categorization, entity-matching, and data-normalization models. Develop scalable ML pipelines for training, inference, and deployment. Implement confidence scoring, model monitoring, drift detection, and retraining. Leverage Python, PyTorch, NLP, embeddings, and LLMs where appropriate. Build reliable MLOps infrastructure supporting multiple enterprise customers. Own technical decisions and collaborate with engineering, data science, and product teams. Requirements 6+ years of ML Engineering, Applied AI, or related experience. Strong Python and experience with PyTorch, TensorFlow, or scikit-learn. Proven end-to-end ownership of production ML systems. Experience with classification, NLP, entity matching, or similar modeling challenges. Strong MLOps experience, including deployment, monitoring, and retraining. Experience with AWS, SageMaker, Docker, Kubernetes, or comparable cloud infrastructure. Excellent problem-solving, architecture, and communication skills. Ideal Candidate: An engineer who can independently design, build, deploy, monitor, and improve scalable machine learning systems - not simply train models or maintain existing infrastructure.

Sony Pictures Entertainment is seeking a talented data engineer to join the Insights, Strategy and Analytics (ISA) organization. The ISA team focuses on enhancing analytical capabilities and infrastructure for internal stakeholders across television production, distribution, and marketing. As the world's largest independent studio, Sony Pictures Television produces original content for streaming and linear networks globally, including popular series across various genres. Our series – from dramas like PLURIBUS, THE NIGHT AGENT, THE LAST OF US, and THE BOYS, to comedies like TWISTED METAL and COBRA KAI, to unscripted series like JEOPARDY!, WHEEL OF FORTUNE, and AMERICAN IDOL – are beloved by our fans and customers worldwide. The Data Engineer II designs and builds reliable, scalable ELT pipelines that power analytics, reporting, and AI/ML applications across Sony Pictures Entertainment. Ideal candidates have prior experience supporting data platforms, analytics, or business intelligence initiatives within a film or television studio, streaming platform, broadcast network, or similarly scaled media company. This role contributes to fast-paced, business-facing analytics initiatives, delivering data products and analytical capabilities that support strategic decision-making across the studio. Key Responsibilities Analytics Engineering: Translate complex business requests into robust data models, business metrics, and semantic layers using dbt and SQL. Apply analytics engineering best practices to ensure maintainability, reliability, and performance. Data Engineering: Support the ingestion of new sources into SPE's Snowflake data platform, working closely with central IT and cloud operations teams to define ingestion requirements and validate that pipelines meet business needs and adhere to SPE's data governance and security policies. Cross-Functional Product Delivery: Partner closely with product managers, strategic analysts, data scientists, data visualization teams, and business stakeholders to deliver impactful tools. Collaborate across disciplines to understand business requirements, harmonize data from disparate systems, and create ready-to-use datasets that enable reporting, advanced analytics, and decision-making. "One Team" Mindset: Contribute to a high-performance team, collaborating openly with peers to create a team culture of ownership, accountability, and continuous improvement. Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Business Analytics, or related fields; advanced degrees are a plus. 5+ years in analytics engineering, data engineering, or a related technical role in a production environment. Experience working with data supporting television, film, streaming, advertising-supported video (AVOD), FAST channels, content distribution, audience analytics, or media strategy. Familiarity with business entities, metrics, and datasets common to a television production and distribution studio, including content and title metadata, audience measurement, ratings, and content performance data, talent, production, licensing, and distribution datasets. Experience working with industry data providers such as IMDb, Gracenote, Luminate, Nielsen, or similar sources is highly desirable. Advanced SQL and Python skills. Experience building transformation pipelines in dbt is strongly preferred. Proficiency with modern cloud data platforms (e.g., Snowflake, GCP/BigQuery, AWS/Redshift) and with pipeline orchestration tools. Familiarity with CI/CD workflows, version control, and automated testing frameworks to meet data quality standards. Exposure to generative AI technologies and practical interest in applying AI-driven approaches to data engineering, data quality, metadata management, and analytics workflows. Strong problem-solving skills, attention to detail, and the ability to communicate effectively with both technical and non-technical stakeholders. The anticipated base salary for this position is $1250K to $160K. This role may also qualify for annual incentive and/or comprehensive benefits. The actual base salary offered will depend on a variety of factors, including without limitation, the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location of the position. Sony Pictures Entertainment is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, age, sexual orientation, gender identity, or other protected characteristics. SPE will consider qualified applicants with arrest or conviction records in accordance with applicable law. To request an accommodation for purposes of participating in the hiring process, you may contact us at SPE_Accommodation_Assistance@spe.sony.com.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Shield AI is seeking a Senior Analytics Engineer to lead the design and delivery of trusted data products for Corporate FP&A, Accounting, Program Finance, GTM, and Strategic Finance. You will independently shape analytical solutions, establish shared standards, and turn business priorities into AI-enabled decision support on our Databricks platform. This senior individual contributor role combines hands-on engineering with cross-functional influence and mentorship to expand Finance's impact. What you'll do: Shape the analytics roadmap with Finance and GTM leaders, prioritizing high-impact products and resolving competing requirements. Build governed datasets and semantic models that support reporting, planning, scenario analysis, and strategic decisions. Set modeling and metric standards across domains, exercising judgment on architecture, quality, and maintainability. Develop conversational analytics and AI-enabled workflows, including Databricks Genie, grounded in trusted business context. Use AI coding assistants to accelerate delivery and explore new capabilities while maintaining rigorous validation and quality. Own business-facing reconciliation and acceptance, partnering with data engineering on reliable delivery. Mentor engineers and Finance partners, strengthening technical practices and self-service capabilities. Required qualifications: Substantial experience in analytics engineering, BI engineering, or financial data modeling, with advanced SQL and a record of delivering production data products. Demonstrated ability to lead ambiguous, cross-functional work from problem definition through adoption. Proficiency with AI coding assistants and sound judgment when reviewing generated work. Practical experience with AI-assisted analytics, ideally Databricks Genie; adjacent Snowflake Cortex or comparable experience is welcome. Sound architectural judgment, disciplined development practices, and experience mentoring others and influencing senior stakeholders. Preferred qualifications: Experience with Databricks, Python, semantic layers, or AI application development. Experience supporting FP&A, GTM, Strategic Finance, Accounting, or Program Finance. Familiarity with enterprise planning, financial controls, or high-growth business environments. $120,000 - $190,000 a year #LC Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Description Full-Time | Remote or Draper, UT Campus (Hybrid) Join Us in Transforming Healthcare Education At Joyce University, the work we do goes beyond technology—it helps move the University forward and supports our mission of preparing people to serve as competent professionals, advance their careers, and pursue lifelong learning. We are seeking an Analytics Engineer to help build the trusted data foundation that enables reporting, insights, and data-driven decision-making across Joyce University. In this role, you will transform data from multiple sources into clean, reliable, analytics-ready datasets and develop the models, metrics, and tools that help teams understand and use data effectively. You will work closely with teams across the University to understand their reporting and analytical needs and translate those needs into scalable data models, standardized metrics, and meaningful insights. Your work will help support self-service analytics, institutional reporting, strategic planning, and everyday decision-making. This is an opportunity to play an important role in helping a growing university turn data into insights that advance healthcare education and support the student journey. What You'll Do Data Modeling & Analytics Engineering Design, build, and maintain analytics-ready data models that support reporting, dashboards, and advanced analysis Transform raw data from multiple sources into clean, reliable, and well-documented datasets Translate business requirements into technical data models, metrics, and KPIs Develop and maintain semantic layers, standardized metrics definitions, and documentation Optimize data models for performance, scalability, and long-term maintainability Contribute to analytics engineering standards, tooling, and data governance practices Data Collection & Processing Extract, transform, and load (ETL) data from diverse data sources and systems Build and maintain automated pipelines, scripts, and workflows for data ingestion and transformation Partner closely with data engineers to define data pipelines, schemas, and best practices Data Analysis & Interpretation Perform exploratory data analysis to identify trends, patterns, and anomalies Apply statistical, analytical, and modeling techniques to generate actionable insights Data Visualization & Reporting Design and deliver interactive dashboards, and reports for stakeholders Communicate insights clearly to both technical and non-technical audiences Enable self-service analytics by supporting business users with trusted datasets and metrics Data Quality & Reliability Ensure data quality, consistency, and reliability through testing, validation, and monitoring Identify, investigate, and resolve data discrepancies and quality issues Implement data quality controls to support accurate and trustworthy analytics What We Offer At Joyce, we believe great work starts with an environment where people feel trusted, supported, and connected to a meaningful purpose. Self-directed paid time off 12 paid holidays Medical, dental, and vision insurance Employer-paid short-term and long-term disability coverage 401(k) retirement plan Professional development opportunities Continuing education opportunities A mission-driven environment focused on healthcare education and student success The flexibility to work fully remote or in a hybrid arrangement from our Draper, Utah campus Requirements What You'll Bring We welcome candidates who bring strong analytical and technical skills, curiosity, and a commitment to making data useful and accessible. You should enjoy connecting business questions with data solutions and be comfortable working independently while partnering with technical and non-technical colleagues across the University. Required Qualifications Bachelor's degree in a quantitative field or equivalent practical experience Strong SQL skills and experience working with relational data models Experience with data transformation tools, such as dbt or similar frameworks Experience transforming raw data into clean, reliable, and well-documented datasets Familiarity with modern data warehouses and ELT/ETL pipelines Solid understanding of data modeling, metrics design, and data quality best practices Experience translating business requirements into scalable analytical solutions Strong analytical thinking, attention to detail, and communication skills What You'll Love About Joyce At Joyce, we believe meaningful work and a great employee experience go hand in hand. Here, you'll find a community that cares about the work we do, the people we serve, and the people we work alongside. Purposeful Work – Your work helps turn data into insights that support the people, systems, and decisions that move healthcare education forward and ultimately make a difference for our students. A Culture of Care – We believe in treating people with warmth, respect, and genuine care. Unreasonable Hospitality is the floor, not the ceiling. Flexibility & Trust – We trust our people to do great work. This role offers the flexibility to work fully remote or in a hybrid arrangement from our Draper, Utah campus. Learning & Growth – We believe learning never stops. You'll have opportunities to build your skills, pursue professional development, and grow alongside a University that is continuing to evolve. People Who Care – You'll work with talented, collaborative colleagues who are committed to helping one another succeed and creating a positive experience for our students and each other. A Growing University – Joyce is a place where your ideas can make an impact. As we grow and innovate, you'll have opportunities to help shape how we work and build what comes next. Work That Matters – Every interaction moves the student forward. No matter your role, the work you do at Joyce contributes to preparing the next generation of healthcare professionals. About Joyce University Joyce University of Nursing & Health Sciences is committed to preparing people to serve as competent professionals, advance their careers, and pursue lifelong learning. Founded in 1979, Joyce has grown into a leading healthcare education institution with pre- and post-licensure programs designed to prepare students for meaningful careers in healthcare. We are a community that values Service, Learning, Integrity, Caring, and Excellence , and we believe every interaction has the opportunity to move the student journey forward.

Established in 2021, Independence Pet Holdings is a corporate holding company that manages a diverse and broad portfolio of modern pet health brands and services, including insurance, pet education, lost recovery services, and more throughout North America. We believe pet insurance is more than a financial product and build solutions to simplify the pet parenting journey and help improve the well-being of pets. As a leading authority in the pet category, we operate with a full stack of resources, capital, and services to support pet parents. Our multi-brand and omni-channel approach include our own insurance carrier, insurance brands and partner brands. About Clarus Clarus, a Doubtless company, is a pioneering pet health technology company transforming the future of pet healthcare. We develop connected solutions across the pet health landscape, helping veterinary teams and pet owners make more informed care and financial decisions. Together, we are reducing complexity and helping more pets receive the care they need. About The Role Clarus is seeking an experienced Analytics Engineer to join the Analytics team. This individual will own the analytics engineering process and serve as the technical bridge between Data Engineering and Analytics delivery. They will build, expand, and optimize Clarus's analytics architecture and pipelines, improving how data flows from diverse sources to downstream analytics solutions. In this role, you will lead high-impact data product and solutions initiatives from ambiguous problem definition through technical design, implementation, rollout, and adoption. You will transform raw and curated data into reliable, analytics-ready models and consistent business metrics using dbt, SQL, Python, and Databricks, while establishing a scalable architecture and strong engineering practices. The ideal candidate is a seasoned analytics engineer with strong data-wrangling skills and a passion for building and optimizing scalable analytics systems. They are self-directed, comfortable supporting multiple projects, systems, and products, and able to set technical direction while remaining deeply hands-on. What You'll Do Own analytics engineering work, including its roadmap, priorities, standards, and operating practices. Design and evolve analytics architecture, with clear responsibilities and quality expectations across bronze, silver, and gold data layers. Build, maintain, and optimize dbt models that transform source data into curated, reusable, analytics-ready datasets. Write and optimize advanced SQL, and use Python for data transformation, validation, automation, and complex processing where appropriate. Develop dimensional and business-oriented data models that support dashboards, self-service analysis, operational reporting, and data products. Establish and document shared KPI definitions, calculation logic, data contracts, ownership, and authoritative sources. Implement automated tests, source freshness checks, documentation, lineage, and monitoring to make data quality visible and dependable. Establish disciplined development practices, including Git-based version control, code review, CI/CD, and controlled promotion across environments. Partner with Data Engineering on ingestion, source schemas, platform performance, and reliable handoffs between foundational and analytical data layers. Partner with analysts, BI developers, and business stakeholders to translate requirements into scalable models rather than one-off reporting logic. Improve Databricks performance and cost efficiency through thoughtful table design, incremental processing, query optimization, and compute usage. Lead data-quality investigations, root-cause analysis, remediation, and communication when critical analytics assets do not meet expectations. Strengthen data governance by applying appropriate access controls, handling sensitive data responsibly, and supporting consistent ownership and stewardship. Migrate duplicated spreadsheet, dashboard, and ad hoc query logic into governed, tested, and reusable dbt models. Design resilient models that support historical analysis, changing source systems, incremental loads, and evolving business definitions. Create clear technical documentation, modeling conventions, and enablement materials that drive adoption of trusted data assets. Raise analytics engineering capability across the team through design reviews, reusable patterns, thoughtful feedback, and hands-on mentorship. What You Bring Bachelor's degree or higher in computer science, data engineering, analytics, information systems, mathematics, or a related discipline, or equivalent professional experience. A strong record of success leading complex analytics engineering, data engineering, business intelligence engineering, or closely related initiatives. Experience in animal health, veterinary services, pet insurance, SaaS, fintech, or health technology is a plus. 8+ years of relevant data and analytics experience, including senior-level ownership of production analytics data models and standards. Advanced SQL skills and demonstrated experience designing, debugging, and optimizing complex transformations. Deep, hands-on dbt experience, including scalable model architecture, testing, incremental models, snapshots, documentation, macros, packages, and production deployment workflows. Strong Databricks experience, including Delta Lake, Spark SQL, Workflows or Jobs, Unity Catalog, and performance management / tuning. Demonstrated skill operating medallion architectures and lakehouse data models across bronze, silver, and gold layers. Strong Python skills for data processing, testing, validation, automation, and engineering utilities. Strong understanding of dimensional modeling, warehouse and lakehouse design, semantic layers, slowly changing dimensions, and metric governance. Experience with modern engineering practices, including Git, CI/CD, code review, automated testing, orchestration, and environment management. Ability to translate ambiguous business needs into clear technical designs and communicate effectively with senior leaders and non-technical stakeholders. What Will Help You Succeed You are intellectually curious, resourceful, and motivated to understand how the business works. You take initiative, identify needs early, and you are comfortable operating in an evolving, high-growth environment. You can move easily between hands-on analytics engineering, and stakeholder conversations. You can manage production data deliverables while continuing to improve the underlying processes. You build trust by producing reliable data products, communicating clearly, and following through on commitments. LOCATION This is a remote U.S. position aligned to Eastern or Central Time business hours. U.S. travel may be required. Compensation Chicago/Boston Base pay range: $123,774 – $154,718 per year NYC Base pay range: $135,026 - $168,784 per year Miami Base pay range: $118,148 - $147,686 Nationwide Base pay range: $112,522 - 140,653 per year This is the range we reasonably expect to pay at hire. Placement within the range depends on job-related factors such as experience, skills, and certifications. This position is eligible for an annual bonus. Base pay is one part of a total rewards package that includes the benefits listed below. All of our jobs come with great benefits including healthcare, parental leave and opportunities for career advancements. Some offerings are dependent upon the location of where you work and can include the following: Comprehensive full medical, dental and vision Insurance Basic Life Insurance at no cost to the employee Company paid short-term and long-term disability 12 weeks of 100% paid Parental Leave Health Savings Account (HSA) Flexible Spending Accounts (FSA) Retirement savings plan Personal Paid Time Off Paid holidays and company-wide Wellness Day off Paid time off to volunteer at nonprofit organizations Pet friendly office environment Commuter Benefits Group Pet Insurance On the job training and skills development Employee Assistance Program (EAP) Interview Technology Notice Please note that phone and video interviews or screenings may be recorded and transcribed using interview technology to support our recruitment process. By continuing with the interview, you consent to this use. Text Messaging Notice If you provide a mobile phone number, you may receive job-related communications via text message. Message and data rates may apply. You may opt out of text communications at any time by replying "STOP."

Established in 2021, Independence Pet Holdings is a corporate holding company that manages a diverse and broad portfolio of modern pet health brands and services, including insurance, pet education, lost recovery services, and more throughout North America. We believe pet insurance is more than a financial product and build solutions to simplify the pet parenting journey and help improve the well-being of pets. As a leading authority in the pet category, we operate with a full stack of resources, capital, and services to support pet parents. Our multi-brand and omni-channel approach include our own insurance carrier, insurance brands and partner brands. About Clarus Clarus, a Doubtless company, is a pioneering pet health technology company transforming the future of pet healthcare. We develop connected solutions across the pet health landscape, helping veterinary teams and pet owners make more informed care and financial decisions. Together, we are reducing complexity and helping more pets receive the care they need. About The Role Clarus is seeking an experienced Analytics Engineer to join the Analytics team. This individual will own the analytics engineering process and serve as the technical bridge between Data Engineering and Analytics delivery. They will build, expand, and optimize Clarus's analytics architecture and pipelines, improving how data flows from diverse sources to downstream analytics solutions. In this role, you will lead high-impact data product and solutions initiatives from ambiguous problem definition through technical design, implementation, rollout, and adoption. You will transform raw and curated data into reliable, analytics-ready models and consistent business metrics using dbt, SQL, Python, and Databricks, while establishing a scalable architecture and strong engineering practices. The ideal candidate is a seasoned analytics engineer with strong data-wrangling skills and a passion for building and optimizing scalable analytics systems. They are self-directed, comfortable supporting multiple projects, systems, and products, and able to set technical direction while remaining deeply hands-on. What You'll Do Own analytics engineering work, including its roadmap, priorities, standards, and operating practices. Design and evolve analytics architecture, with clear responsibilities and quality expectations across bronze, silver, and gold data layers. Build, maintain, and optimize dbt models that transform source data into curated, reusable, analytics-ready datasets. Write and optimize advanced SQL, and use Python for data transformation, validation, automation, and complex processing where appropriate. Develop dimensional and business-oriented data models that support dashboards, self-service analysis, operational reporting, and data products. Establish and document shared KPI definitions, calculation logic, data contracts, ownership, and authoritative sources. Implement automated tests, source freshness checks, documentation, lineage, and monitoring to make data quality visible and dependable. Establish disciplined development practices, including Git-based version control, code review, CI/CD, and controlled promotion across environments. Partner with Data Engineering on ingestion, source schemas, platform performance, and reliable handoffs between foundational and analytical data layers. Partner with analysts, BI developers, and business stakeholders to translate requirements into scalable models rather than one-off reporting logic. Improve Databricks performance and cost efficiency through thoughtful table design, incremental processing, query optimization, and compute usage. Lead data-quality investigations, root-cause analysis, remediation, and communication when critical analytics assets do not meet expectations. Strengthen data governance by applying appropriate access controls, handling sensitive data responsibly, and supporting consistent ownership and stewardship. Migrate duplicated spreadsheet, dashboard, and ad hoc query logic into governed, tested, and reusable dbt models. Design resilient models that support historical analysis, changing source systems, incremental loads, and evolving business definitions. Create clear technical documentation, modeling conventions, and enablement materials that drive adoption of trusted data assets. Raise analytics engineering capability across the team through design reviews, reusable patterns, thoughtful feedback, and hands-on mentorship. What You Bring Bachelor's degree or higher in computer science, data engineering, analytics, information systems, mathematics, or a related discipline, or equivalent professional experience. A strong record of success leading complex analytics engineering, data engineering, business intelligence engineering, or closely related initiatives. Experience in animal health, veterinary services, pet insurance, SaaS, fintech, or health technology is a plus. 8+ years of relevant data and analytics experience, including senior-level ownership of production analytics data models and standards. Advanced SQL skills and demonstrated experience designing, debugging, and optimizing complex transformations. Deep, hands-on dbt experience, including scalable model architecture, testing, incremental models, snapshots, documentation, macros, packages, and production deployment workflows. Strong Databricks experience, including Delta Lake, Spark SQL, Workflows or Jobs, Unity Catalog, and performance management / tuning. Demonstrated skill operating medallion architectures and lakehouse data models across bronze, silver, and gold layers. Strong Python skills for data processing, testing, validation, automation, and engineering utilities. Strong understanding of dimensional modeling, warehouse and lakehouse design, semantic layers, slowly changing dimensions, and metric governance. Experience with modern engineering practices, including Git, CI/CD, code review, automated testing, orchestration, and environment management. Ability to translate ambiguous business needs into clear technical designs and communicate effectively with senior leaders and non-technical stakeholders. What Will Help You Succeed You are intellectually curious, resourceful, and motivated to understand how the business works. You take initiative, identify needs early, and you are comfortable operating in an evolving, high-growth environment. You can move easily between hands-on analytics engineering, and stakeholder conversations. You can manage production data deliverables while continuing to improve the underlying processes. You build trust by producing reliable data products, communicating clearly, and following through on commitments. LOCATION This is a remote U.S. position aligned to Eastern or Central Time business hours. U.S. travel may be required. Compensation Chicago/Boston Base pay range: $123,774 – $154,718 per year NYC Base pay range: $135,026 - $168,784 per year Miami Base pay range: $118,148 - $147,686 Nationwide Base pay range: $112,522 - 140,653 per year This is the range we reasonably expect to pay at hire. Placement within the range depends on job-related factors such as experience, skills, and certifications. This position is eligible for an annual bonus. Base pay is one part of a total rewards package that includes the benefits listed below. All of our jobs come with great benefits including healthcare, parental leave and opportunities for career advancements. Some offerings are dependent upon the location of where you work and can include the following: Comprehensive full medical, dental and vision Insurance Basic Life Insurance at no cost to the employee Company paid short-term and long-term disability 12 weeks of 100% paid Parental Leave Health Savings Account (HSA) Flexible Spending Accounts (FSA) Retirement savings plan Personal Paid Time Off Paid holidays and company-wide Wellness Day off Paid time off to volunteer at nonprofit organizations Pet friendly office environment Commuter Benefits Group Pet Insurance On the job training and skills development Employee Assistance Program (EAP) Interview Technology Notice Please note that phone and video interviews or screenings may be recorded and transcribed using interview technology to support our recruitment process. By continuing with the interview, you consent to this use. Text Messaging Notice If you provide a mobile phone number, you may receive job-related communications via text message. Message and data rates may apply. You may opt out of text communications at any time by replying "STOP."

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.

Job Requisition ID # 26WD101382 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.

Job Description Providing for loved ones, planning rewarding retirements, saving enough for whatever lies ahead – our policyholders count on us to be there when it matters most. It's a big ask, but it's one that we have the power to deliver when we work together. We collaborate and innovate – pushing one another to transform not just Pacific Life, but the entire industry for the better. Why? Because it's the right thing to do. Pacific Life is more than a job; it's a career with purpose. It's a career where you have the support, balance, and resources to make a positive impact on the future – including your own. We're actively seeking a talented Analytics Engineer to join our Analytics Engineering team as part of our Advanced Analytics function in our Newport Beach, CA office. Reporting to the Director, Analytics Engineering, this role will help transform enterprise data into trusted, reusable analytics products that support reporting, machine learning, data science, and AI-powered business solutions. You'll collaborate with business stakeholders, analytics delivery, data engineers, visualization engineers, and data scientists to translate business needs into tested, documented, and scalable analytical models. Our work goes beyond building data transformations. We capture the business definitions, rules, and relationships that make data meaningful and usable by both people and AI agents. Working with dbt, Snowflake, Snowflake Cortex, AWS, and modern engineering practices, you'll help deliver reliable analytics solutions while enabling stakeholders to confidently use data and AI. You'll also contribute to our adoption of AI-assisted and agentic development using tools such as Claude Code and GitHub Copilot, with appropriate testing, human review, and security controls. How you will help move us forward Analytics Engineering: Develop and maintain modular SQL transformations and analytical data models using dbt and Snowflake, creating reusable data sets for reporting, analysis, data science, and AI use cases. Business Context and Semantic Modeling: Partner with stakeholders to understand business processes and translate requirements into clear data definitions, business rules, metrics, and semantic models. Document relationships and assumptions so data can be interpreted consistently. Data Quality and Trust: Build automated tests, validate business logic, investigate discrepancies, and maintain documentation and lineage to help ensure analytical data is accurate, understandable, and reliable. AI and Agentic Solutions: Contribute to the development, testing, and evaluation of Snowflake Cortex solutions and AI agents grounded in trusted enterprise data and business context. Modern Development Practices: Use Git, Azure DevOps (ADO), and CI/CD workflows to manage work, collaborate through pull requests, automate validation, and deliver controlled changes across development and production environments. AI-Assisted and Agentic Development: Apply approved tools such as Claude Code and GitHub Copilot to development, testing, documentation, and workflow automation. Review and validate AI-generated outputs while following engineering, privacy, and security standards. Stakeholder Enablement: Provide hands-on guidance, demonstrations, documentation, and knowledge transfer that help business partners adopt analytics products, use Snowflake Cortex, and become more self-sufficient. Reliability and Continuous Improvement: Troubleshoot analytical models and workflows, improve query performance and efficiency, modernize manual processes, and contribute reusable patterns and improvements to the team's engineering playbook. Cross-Functional Collaboration: Work with data engineering, platform, governance, and technology partners to deliver solutions that align with enterprise architecture, access controls, and operational standards, including AWS-based components where applicable. The experience you bring Education: Bachelor's degree in Computer Science, Information Systems, Data Analytics, Mathematics, Engineering, or a related field, or equivalent practical experience. Professional Experience: Typically at least 2–5 years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical role. Core Stack Experience: Hands-on professional experience with dbt and Snowflake, including developing, testing, documenting, and maintaining analytical data models. SQL and Data Modeling: Strong SQL skills and practical understanding of relational and dimensional modeling, data transformation, business logic, and query optimization. Software Engineering Practices: Experience with Git version control, branching, pull requests, code reviews, automated testing, and CI/CD. Experience with Azure DevOps (ADO) or a comparable delivery platform. Programming and Cloud: Working knowledge of Python for scripting, automation, or data-related development. Familiarity with AWS and cloud-based data environments; professional AWS experience is preferred. Business Partnership: Ability to translate business questions into technical requirements, explain technical concepts clearly, and help stakeholders understand and use analytical solutions. Problem Solving and Ownership: A thoughtful, detail-oriented approach to troubleshooting, validating results, documenting decisions, and following work through delivery. AI and Emerging Tools: Experience with Snowflake Cortex, AI agents, or generative AI solutions is preferred. Familiarity with Claude Code, GitHub Copilot, or other AI-assisted and agentic development tools is a plus, along with a willingness to learn and apply them responsibly. Industry Background: Experience in insurance, financial services, or another regulated environment is preferred, but not required. You can be who you are We are committed to a culture of diversity and inclusion that embraces the authenticity of all employees, partners and communities. We support all employees to thrive and achieve their fullest potential. What's life like at Pacific Life? Visit Instagram.com/lifeatpacificlife. Base Pay Range The base pay range noted represents the company's good faith minimum and maximum range for this role at the time of posting. The actual compensation offered to a candidate will be dependent upon several factors, including but not limited to experience, qualifications and geographic location. Also, most employees are eligible for additional incentive pay. $103,140.00 - $126,060.00 Your Benefits Start Day 1 Your wellbeing is important to Pacific Life, and we're committed to providing you with flexible benefits that you can tailor to meet your needs. Whether you are focusing on your physical, financial, emotional, or social wellbeing, we've got you covered. Prioritization of your health and well-being including Medical, Dental, Vision, and Wellbeing Reimbursement Account that can be used on yourself or your eligible dependents Generous paid time off options including: Paid Time Off, Holiday Schedules, and Financial Planning Time Off Paid Parental Leave as well as an Adoption Assistance Program Competitive 401k savings plan with company match and an additional contribution regardless of participation You Can Be Who You Are We are committed to a culture of diversity and inclusion that embraces the authenticity of all employees, partners and communities. We support all employees to thrive and achieve their fullest potential. What's life like at Pacific Life? Visit Instagram.com/lifeatpacificlife EEO Statement Pacific Life Insurance Company is an Equal Opportunity /Affirmative Action Employer, M/F/D/V. If you are a qualified individual with a disability or a disabled veteran, you have the right to request an accommodation if you are unable or limited in your ability to use or access our career center as a result of your disability. To request an accommodation, contact a Human Resources Representative at Pacific Life Insurance Company.

Reporting to the Director of Technology. An integral part of the ALMAG Aluminium Information Technology Department the Sr. Business Systems & Database Analyst will assist with the planning, organizing, and optimizing the overall operation of business systems at ALMAG. Responsible for technical, operational support and maintenance of critical business systems at ALMAG. Ensure that business systems meet business objectives while maintaining accessible and reliable systems for internal customer use. The incumbent will monitor changes in industry trends, innovations and customer behaviours and identify potential impact and applicability to ALMAG?s strategic, market, sales and functional plans. The incumbent will develop recommendations and once approved, will collaborate and support various teams to design and implement process and enhancements within mission-critical business systems. DUTIES AND RESPONSIBILITIES The duties and responsibilities of the Sr. Business Systems & Database Analyst are detailed below, but not limited to the following: Planning Participate in the review of business processes to generate recommendations for productivity improvements through technology Risk mitigation and planning Work with partners to eliminate redundant or ineffective business procedures Enhance the customer service experience Work with partners to gain agreement on solutions Analyse data to quantify benefits and assess costs Participate in presentations and meetings with Senior Management Participate in the preparation of RFPs, bid proposals, and contracts Work closely with the Director of Technology to develop application architecture and underlying services to run enterprise business systems Research emerging practices and technologies and participate in long-range planning for the development of business systems solutions, evaluating new deployment and migration models and methodologies Operations Develop and implement business systems projects that meet agreed business outcomes Communicate effectively with various partners, setting clear expectations and explaining complex concepts to non-technical audiencesProvide expert guidance with hands-on support to solve complex and challenging business problems to the satisfaction of key partners Plan, develop, and on?time delivery of effective business solutions Coordinate and perform in-depth testing of modified and new systems, including end-user reviews and other post-implementation support Support the organization through the design and implementation of robust training Maintain, administer, and upgrade existing database and application systems as required Ensure the proper management and integrity of ALMAG data Identify and compile metrics from business systems to support data analysis and business improvements Apply methods and techniques to ensure the security of applications and data Responsible for using problem-solving and analytical skills to support the design, implementation, and maintenance of solutions that support the extrusion production system Support the business through the ongoing implementation, configuration, support, and testing of an alternate ERP system Design, deploy, and maintain dashboards ad-hoc reports, perform data analytics, and build data visualization solutions to meet business needs using Power BI or Crystal reporting Develop and maintain dashboards, reports, and data visualizations Create standard operating procedures, support new user onboarding, and train users on system functionality Perform additional duties as required to support the business Governance Collaborate with Busines

Cooke is a global seafood company with operations in North America, Europe, South America and Australia. Our company's success is driven by our dynamic, highly skilled, and innovative management team, supported by dedicated employees who live in coastal communities and contribute to the local area's economy and sense of community. Cooke is continuing to mature its digital strategy through modern data platforms, integrated data pipelines, and enterprise data standards that support operations, processing, distribution, and corporate functions. As a Data Engineer, you will develop and optimize data integration solutions, implement automation, monitor data quality, and collaborate with architects and business teams to align data solutions with enterprise data models. The Role As a Data Engineer, you will design, develop, and optimize data pipelines and transformations that support analytics, operational reporting, and enterprise data integration. You will work independently on routine data engineering activities while partnering with business analysts, architects, application teams, and data stakeholders to deliver reliable, secure, and well-documented data solutions. Key Responsibilities Design, develop, and optimize data pipelines and transformations to support analytics and operational reporting.Implement data validation, cleansing, and quality checks to ensure reliable datasets.Collaborate with business analysts, architects, and application teams to understand and deliver against data requirements.Automate data ingestion and integration processes to improve performance, reliability, and repeatability.Maintain data documentation, metadata, lineage, and technical specifications for ongoing support and reference. What Success Looks Like Reliable ETL and ELT pipelines are built, maintained, and improved with minimal supervision.Data quality checks, cleansing logic, and validation processes are embedded into data workflows.Data requirements are translated into practical solutions through effective collaboration with analysts, architects, and application teams.Ingestion, integration, and orchestration processes are automated where appropriate to improve reliability and performance.Technical documentation, metadata, and lineage remain current and aligned to Cooke's enterprise data standards. Core Skills & Competencies Proficient in building and maintaining ETL and ELT data pipelines using tools such as Snowflake, DBT, FiveTran, Boomi, and API-based integrations.Strong SQL, scripting, and data modelling skills, with the ability to map data flows, lineage, and relationships across source and target systems.Ability to implement ingestion, transformation, orchestration, validation, cleansing, and quality checks independently using standard Cooke tools and patterns.Working knowledge of data warehousing, APIs, integration patterns, data security, metadata management, and governance workflows.Strong troubleshooting and collaboration skills to resolve data quality or performance issues and work effectively with architects, analysts, engineers, and business stakeholders. Behaviors That Drive Success Adaptability: Adjusts work methods for new tools, priorities, or directions with limited guidance.Business Acumen: Applies business insights to improve processes and make informed decisions.Collaboration & Synergy: Builds strong cross-functional relationships and encourages knowledge sharing.Decisiveness: Makes timely, data-informed decisions within scope.Design Thinking: Uses user-centered design and data insights to inform solutions.Digital Acumen: Applies digital insights to improve work quality or customer experience.Diversity Mindset: Values diversity in teams and ensures inclusivity in discussions and decisions.Growth Mindset: Demonstrates continuous learning and encourages it in others.Innovative: Applies innovative methods to solve functional or business challenges.Outcome Driven: Delivers measurable results tied to team or pro