Senior Analytics Engineer, Senior Associate of Morgan Health

Help advance Morgan Health’s mission: better care for JPMorgan Chase plan members and across employer-sponsored insurance.

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

Design CI/CD pipelines and deployment workflows in response to evolving control requirements — not just execute an existing process

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 analytics/modeling, or a closely related role with a focus on building curated, analyst- and data-science-facing datasets

Proficiency in SQL with demonstrated skills and hands-on experience building modular, tested, version-controlled SQL transformations using dbt

Demonstrated ownership of the full lifecycle of a dbt project, including automated testing, CI/CD and deployment, environment/version management, monitoring, and ongoing performance and reliability of the analytics layer in production

Hands-on experience using Databricks (or similar platforms) to develop, deploy, and support data pipelines and analytics workflows in a production environment; experience working with Python or R for analysis, testing, and automation

Proven track record of creating and maintaining data models, data marts, and transformations that support multiple competing analytical use cases

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

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

To be eligible for this role, you must be authorized to work in the United States. We do not offer any type of employment-based immigration sponsorship for this role. Likewise, JPMorgan Chase & Co. will not provide any assistance or sign any documentation in support of any other form of immigration sponsorship or benefit, including optional practical training (OPT) or curricular practical training (CPT).