As a Senior Associate of Analytics Engineering within Morgan Health, you will utilize your deep experience with data warehouses, transformations, and analytics engineering best practices to build and scale a trusted analytics layer that powers Morgan Health’s data science insights. In this role, you will design and maintain curated data marts and measures for use by data scientists and analytical stakeholders. You will lean into your skills as a motivated problem-solver, team collaborator, and clear communicator to play a crucial role in progressing Morgan Health’s mission to improve health care for JPMorganChase health plan members and across employer-sponsored insurance.

Job Responsibilities:

• Build and update Morgan Health’s healthcare data model (e.g., marts and curated datasets) using SQL and dbt.
• Create proof of concept (POC) solutions of data products per data scientist design requirements; iterate rapidly to refine requirements and evolve POCs to production-level solutions.
• Develop and maintain robust automated testing (e.g., dbt tests and custom checks) for new and refreshed datasets.
• Perform code reviews and quality checks of peer work; adhere to coding standards and best practices; incorporate feedback to continuously improve maintainability and reliability.
• Maintain clear documentation (data dictionary, model descriptions, metric logic, known limitations, and issue logs) to promote transparency and support data governance and HIPAA-aligned compliance standards.
• Proactively investigate, identify root causes, and address data quality issues in the analytics layer; partner with the Data Product lead to validate upstream issues and prioritize solutions.
• Contribute to continuous improvement of analytics engineering practices, including CI/CD, development workflows, performance optimization.

Required Qualifications, Capabilities, and Skills:

• Bachelor’s degree in a quantitative field such as computer science, information systems, engineering, or a related discipline
• 5 years of professional experience in analytics engineering, data engineering, or a closely related role
• Proven track record of creating and maintaining data models, data marts, and transformations that support multiple competing analytical use cases
• Strong understanding of data warehousing concepts, dimensional modeling techniques, CI/CD processes, and data quality principles
• Hands-on experience with dbt and strong SQL skills; experience working with Python or R for analysis, testing, or automation
• Motivated to develop clear technical documentation (data dictionaries, lineage notes, model descriptions) that proactively and transparently supports correct downstream data use
• Team-oriented, positive collaborator who brings a constructive attitude and contributes to an inclusive, high-trust environment
• Strong written and verbal communication skills with an ability to effectively interface within cross-functional teams (data scientists, analytics engineering, product/architecture, and platform partners)

Preferred Qualifications, Capabilities, and Skills

• Experience working with health care data (e.g., medical and pharmaceutical claims, eligibility, provider, survey, or biometrics data), common medical groupers, and quality measurement standards
• Advanced degree in a quantitative field such as computer science, information systems, engineering, or a related discipline
• Hands-on experience with Databricks or similar technologies
• Experience using AI-assisted coding tools to develop, test, and improve SQL, Python, and analytics engineering workflows
• Experience supporting analytics platforms in regulated and/or privacy-sensitive environments
• Demonstrated ability to successfully multitask, balance competing priorities, and deliver high-quality work in a fast-paced environment