Data Engineer

Description

Brook is the continuous care infrastructure for healthcare. Building on our foundation in remote care, we provide the connected operating system that combines clinical AI, care teams, connected devices, and end-to-end delivery to enable continuous, longitudinal care at scale.

We support adults managing chronic conditions such as diabetes, hypertension, and heart failure, while also helping people reduce their risk of developing type 2 diabetes through Brook+, our CDC‑recognized Diabetes Prevention Program.

Working alongside clinics, hospitals, and health plans, we help patients stay connected, engaged, and supported between visits through a combination of technology, clinical expertise, and proactive outreach. The approach enables earlier intervention, improves the patient experience, reduces administrative burden on care teams, and helps healthcare organizations deliver better outcomes more efficiently.

The result is healthier patients, more satisfied providers, fewer avoidable hospitalizations, and a more scalable and sustainable approach to chronic care management.

Make continuous care the new standard of healthcare.

Run the continuous care infrastructure that extends clinical teams and empowers patients to achieve better health outcomes.

For our patients. For our partners. For each other.

Our data team is entering a once‑in‑a‑career moment. AI is reshaping how healthcare organizations consume data. The repetitive “pull‑a‑report, answer‑a‑question” work that used to consume analyst teams is being handled increasingly well by AI. That frees the humans on our team to do the work that moves the needle: building the trustworthy data foundation that the AI, the clinicians, and the executives all depend on.

The Data Engineers will sit at the heart of this transformation. The engineer is the business‑intelligence and data‑hygiene engine of the team — understanding the business and make sure analytics flow cleanly from source all the way to the AI that answers the question; not a back‑room pipeline specialists. They build the pipes, they build the models, and they make sure that every answer the AI gives rests on correct, rigorous, auditable data.

This hybrid position is based in Bellevue, WA, with in‑office collaboration Monday through Thursday. Our office is in a great Bellevue location, a 10‑minute walk from the new light rail stop.

Most data engineers today are specialists. This role is for someone who wants to own both pipelines and modeling, because the next generation of data teams will not have the luxury of deep specialization. AI has collapsed the distance between raw data and a stakeholder‑ready answer. The engineers who thrive will be the ones who can think end‑to‑end, care about the business, and hold the semantic layer up as the source of truth the AI depends on.

• Build and maintain batch and streaming pipelines that move PGHI protected data, data, device telemetry, billing, growth and operational data into our cloud warehouse.
• Own orchestration (Airflow, Dagster, or Prefect) and warehouse‑loading layers with production‑grade reliability.
• Partner on HIPAA‑aligned data handling: encryption, access controls, audit trails, PHI segregation.

• Shape raw data into clean, documented dbt models: staging, marts, tests, and lineage.
• Define canonical metrics — adherence, monitoring minutes, alert response time, deterioration risk signals — in partnership with clinical and operations stakeholders.
• Own the semantic layer (dbt Semantic Layer, Cube, Metric Flow, or similar) that grounds both traditional analytics and AI‑driven queries.

• Ship test coverage, anomaly detection, and data contracts with upstream systems.
• Document models, metric lineage, and validation logic thoroughly — your docs are the substrate the AI uses to answer questions accurately.
• Own reliability: monitoring, alerting, incident response, and backfills.

• Partner directly with our Applied AI function to ensure…