Senior Analytics Engineer, Senior Associate of Morgan Health

Morgan Health is a mission-driven healthcare organization within JPMorgan Chase focused on improving the quality, affordability, and experience of employer-sponsored healthcare.

We operate with the focus and agility of a smaller, specialized team, backed by the scale, resources, and reach of one of the world's largest companies.

Our team brings together healthcare, data, research, investment, and policy expertise to tackle some of the most complex challenges facing employers and their employees.

If you are someone who wants their technical work to have a tangible impact on healthcare, this is a unique opportunity to build within a highly collaborative team to further Morgan Health's mission.

As a Senior Analytics Engineer within Morgan Health, you'll play a key role in building the data foundation behind that work.

You'll have meaningful ownership of Morgan Health's analytics environment, partnering closely with data scientists as well as other internal and external stakeholders to turn complex healthcare data into trusted, production-ready data marts that support research, insights, and decision-making.

In this role, you will have the opportunity to shape how analytics engineering is done within Morgan Health - not simply inherit an established process.

You will own and evolve core elements of the analytics life cycle, from data modeling and testing to CI/CD, monitoring and quality standards.

Because we're a focused team, you will work closely with the people using the data and have visibility into how your work contributes to healthcare research, insights, and ultimately better outcomes.

This role is in-office five days per week, based in either New York, NY or Washington, DC.

Job Responsibilities:


* Develop and maintain Morgan Health's healthcare data models (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


* Design and evolve a robust automated testing framework (e.g., dbt tests, custom checks, risk-based testing strategies)


* Design, deploy, and maintain Databricks bundles and production jobs using environment branching strategies, and integrate with Unity Catalog to ensure an access-controlled, auditable data asset management


* Lead code reviews and establish quality standards for the team's dbt codebase; enforce best practices and drive continuous improvement in code-review rigor, traceability, and maintainability


* 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


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