Data Engineer

Brook Inc • Bellevue, WA

7d • $130,000 - $150,000 • Hybrid

About The Position

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, and help 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. This 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. Our ambition is to make continuous care the new standard of healthcare and run the continuous care infrastructure that extends clinical teams and empowers patients to achieve better health outcomes. Brook. The Remote Care Company. For our patients. For our partners. For each other.

Requirements

• 4+ years building production data pipelines and/or modeling data in dbt.
• Strong Python and SQL.
• Production experience with a modern cloud warehouse (Snowflake, BigQuery, or Databricks).
• Hands-on dbt and dimensional or semantic-layer data modeling experience.
• A track record of owning reliability — not just shipping features, but keeping data flowing cleanly over time.
• Daily production use of Claude or comparable LLM assistants — effective prompting, output verification, and agent chaining.
• Clear written and verbal communication with both technical and non-technical partners.
• Comfort handling PHI in a HIPAA-aligned environment.
• Bias toward automation over toil.
• Skeptical rigor with AI output — trust through verification.
• Curiosity about the healthcare operations beneath the data.
• End-to-end ownership instinct: ingestion, modeling, quality, and the AI layer that sits on top.

Nice To Haves

• Healthcare data experience: HL7, FHIR, claims, EHR extracts, or device telemetry.
• Exposure to LLM-driven analytics patterns — text-to-SQL, RAG over metrics, or metric grounding for AI.
• Streaming experience: Kafka, Kinesis, or Pub/Sub — for real-time vitals and alerts.
• Infrastructure-as-code fluency (Terraform or equivalent).
• MCP servers, agentic workflows, or LLM automations.
• Experience shipping alongside data scientists or ML engineers.
• Early-stage or high-growth startup background.

Responsibilities

• 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, MetricFlow, 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 every LLM answer is anchored in your data models and canonical metrics.
• Evaluate AI query outputs against ground-truth metrics and help close the loop when the model gets things wrong.
• Help shape how the data team itself uses AI tooling (Claude, Claude Code, Cursor, Copilot) in day-to-day work.
• Work closely with others on the data team, care, product, operations, growth and leadership stakeholders to define what the data needs to say.

Benefits

• Medical, dental, and vision — Brook pays 100% of premiums for you and your children and 50% for a spouse or domestic partner, plus a Brook-funded HSA contribution (prorated by hire date) and a medical concierge.
• Mental health at no cost through Spring Health, plus flexible PTO, dedicated sick time, and a generous holiday schedule.
• Employer-paid life, AD&D, and short- and long-term disability; 401(k) with company match; and an emergency-savings match.
• Employee referral bonus.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed