Senior Analytics Engineer - Health Data Platform

JPMorganChase; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorganChase’s Morgan Health is seeking a Senior Associate of Analytics Engineering based in New York, NY or Washington, DC. You will design and maintain curated data marts and measures, building scalable SQL-based data products to power data science insights.

You will own dbt-driven transformations, automated testing, and CI/CD, collaborate with data scientists and platform partners, and help ensure data quality, governance, and HIPAA-aligned compliance across the analytics layer.

Qualifications

• Bachelor's degree in a quantitative field such as computer science, information systems, engineering, or 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.
• Strong SQL skills and hands-on experience building modular, tested, version-controlled SQL transformations using dbt or other transformation or semantic-layer tools.
• 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.
• Experience working with Python or R for analysis, testing, or automation.
• Proven track record of creating and maintaining data models, data marts, and transformations that support multiple competing analytical use cases.
• Demonstrated ownership of the full lifecycle of a dbt project, including workflow design, automated testing, CI/CD and deployment, environment/version management, monitoring, and ongoing performance and reliability of the analytics layer in production.
• 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).

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.

Skills

SQL

dbt

Python/R

Data modeling

Data governance

CI/CD

Documentation

Team collaboration

Communication

Education

Bachelor's degree in a quantitative field

Advanced degree in a quantitative field

Tools

dbt

SQLMesh

Dataform

Coalesce

Matillion

Databricks

Job description

JPMorganChase’s Morgan Health is seeking a Senior Associate of Analytics Engineering based in New York, NY or Washington, DC. You will design and maintain curated data marts and measures, building scalable SQL-based data products to power data science insights.

You will own dbt-driven transformations, automated testing, and CI/CD, collaborate with data scientists and platform partners, and help ensure data quality, governance, and HIPAA-aligned compliance across the analytics layer.