Staff Data Engineer

Cityblock Health

20d•$153,000 - $210,000

About The Position

Cityblock delivers value-based care to individuals with complex needs, focusing on Medicaid beneficiaries and dual eligibles. This role is crucial for building the data foundation that enables accurate reasoning over data for both human and AI decision-making. The engineer will own significant parts of the data pipeline, ensuring it can be leveraged at scale to provide consistent answers for member care. The role involves working with dbt Mesh on BigQuery (GCP), with data ingestion orchestrated by Dagster. The data includes claims (medical and pharmacy), eligibility and enrollment, EHR, HIE/FHIR feeds, and data from Cityblock's care management platform and vendor systems, all feeding into a semantic layer. The engineer will treat data quality as a product, focusing on improving member identity and eligibility data, building and maintaining ingest and transformation systems for raw partner data, and owning the reverse-ETL layer that impacts operational efficiency. Additionally, the role supports clinical performance evaluation and value-based contracts through a quality measurement pipeline for HEDIS and Stars metrics. The engineer will also define and maintain the semantic and metrics layer for consistent metric definitions, make metrics machine-readable for AI agents, and build self-serve analytics. Collaboration with Applied AI, BI, clinical stakeholders, and the platform team is essential.

Requirements

6+ years of experience as an engineer who builds trustworthy systems.
Hands-on experience with dbt and SQL at production scale.
Experience with orchestration using Dagster, Airflow, or equivalent.
Experience owning operational or reverse-ETL data systems that other applications depend on in production.
Experience designing or maintaining a semantic layer or a metrics layer.
Understanding of how LLMs consume structured context.
Fluent daily use of AI assistants tooling (Claude, Cursor, Codex, or equivalent) for engineering and within data analytics.
Demonstrated ability to scale AI adoption to accelerate collaborative work.
Drawn to mission-oriented work.
Comfortable partnering with BI, clinical, and product stakeholders whose expertise differs from yours.

Nice To Haves

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

Responsibilities

Improve the quality of member identity and eligibility data.
Build and maintain ingest and transformation systems for raw partner data.
Own the reverse-ETL layer that feeds operational data.
Support clinical performance evaluation and value-based contracts through a quality measurement pipeline.
Define and maintain the semantic and metrics layer.
Make metrics machine-readable and well-constrained for AI agents.
Build self-serve analytics for stakeholders.
Feed the Applied AI product work with grounded, trustworthy context.
Partner with BI and clinical stakeholders to align semantic layer definitions with business reasoning.
Work with the platform team to ensure governed data querying paths.