Staff Data Engineer

Cityblock Health, Inc. is hiring a Staff Data Engineer to own and strengthen data pipelines and systems that support care delivery, analytics, and AI. The role focuses on reliable operational data, a governed semantic and metrics layer, and self-serve analytics in partnership with BI, clinical, product, and platform teams.

Responsibilities:

• You'll improve the quality of member identity and eligibility data that determines who is an active member and gates every downstream clinical and financial workflow
• Build and maintain the ingest and transformation systems that turn raw partner data into something dependable, from correctness through freshness to reliability
• Own the reverse-ETL layer that feeds the operational data that directly impacts the efficiency and effectiveness of the execution of Cityblock's care model
• Support clinical performance evaluation and value-based contracts through a quality measurement pipeline that produces HEDIS and Stars metrics
• Define and maintain the semantic and metrics layer so each metric has one correct definition, applied consistently across every dashboard and every consumer
• Make metrics machine-readable and well-constrained, so an AI agent querying them gets a correct answer because the layer bounds what it can conclude
• Build self-serve analytics so stakeholders can answer their own questions against definitions they can trust
• Feed the Applied AI product work the grounded, trustworthy context its features depend on
• Partner with BI and clinical stakeholders so the definitions in the semantic layer match how the business actually reasons about itself
• Work with the platform team so agents query your data through governed, well-understood paths

Requirements:

• 6+ years of experience as an engineer who builds trustworthy systems
• Hands-on experience with dbt and SQL at production scale including orchestration with 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
• An understanding of how LLMs consume structured context and fluent daily use of AI assistants tooling (Claude, Cursor, Codex, or equivalent) for engineering and within data analytics
• A demonstrated ability to scale AI adoption to accelerate collaborative work with your peers
• Drawn to mission-oriented work, and comfortable partnering with BI, clinical, and product stakeholders whose expertise differs from yours
• 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