Staff Data Engineer

Cityblock Health

3d•$153,000 - $210,000

About The Position

Cityblock is hiring a Staff Data Engineer to own major parts of the data foundation that enables people and AI systems to reason correctly over data and support care for members. The role works across a dbt Mesh on BigQuery (GCP), with ingestion orchestrated through Dagster, and handles claims, eligibility and enrollment rosters, EHR data, HIE/FHIR feeds, internally developed care-management platform data, and vendor-system data through to the semantic layer. The position treats data quality as a product. It owns and improves data pipelines and systems that support operational workflows, clinical performance evaluation, value-based contracts, metrics, self-serve analytics, and Applied AI products. The engineer partners with BI, clinical, product, and platform stakeholders to ensure metrics and data definitions are trustworthy, consistent, machine-readable, and usable through governed paths.

Requirements

At least 6 years of experience as an engineer building trustworthy systems.
Hands-on production-scale experience with dbt and SQL, including orchestration with Dagster, Airflow, or an equivalent tool.
Experience owning operational or reverse-ETL data systems on which other production applications depend.
Experience designing or maintaining a semantic layer or metrics layer.
Understanding of how LLMs consume structured context.
Fluent daily use of AI assistant tooling such as Claude, Cursor, Codex, or equivalent for engineering and data analytics.
Demonstrated ability to scale AI adoption to accelerate collaborative work with peers.
Interest in mission-oriented work and comfort partnering with BI, clinical, and product stakeholders with different areas of expertise.

Nice To Haves

A computer science degree or equivalent.
Prior experience in a regulated or compliance-heavy environment, such as HIPAA or SOC 2.
Direct experience with BigQuery.
Exposure to healthcare and clinical data, including ADT, HEDIS, and CMS Stars.
Experience building self-serve analytics adopted by non-technical stakeholders.

Responsibilities

Improve member identity and eligibility data quality, including data that determines active membership and gates downstream clinical and financial workflows.
Build and maintain ingestion and transformation systems that make raw partner data dependable in correctness, freshness, and reliability.
Own the reverse-ETL layer that feeds operational data used by Cityblock’s care model.
Support clinical performance evaluation and value-based contracts through a quality measurement pipeline producing HEDIS and Stars metrics.
Define and maintain the semantic and metrics layer so metrics have consistent definitions across dashboards and consumers.
Make metrics machine-readable and well-constrained so AI agents can query them correctly.
Build self-serve analytics that let stakeholders answer questions using trusted definitions.
Provide Applied AI product work with grounded, trustworthy context.
Partner with BI and clinical stakeholders to align semantic-layer definitions with how the business reasons about itself.
Work with the platform team to ensure agents query data through governed, well-understood paths.
Use AI assistant tools to accelerate engineering and data analytics work and scale AI adoption with peers.