About the Role
You will be our first full-time data engineer and our only data hire for the foreseeable future. You will own the whole data function: pipelines, data infrastructure and reporting for every team in the company. You won't start from scratch. We already run BigQuery and dbt, with hourly ingestion from our EHR, marketing attribution, and a set of Metabase dashboards, built by a part-time data engineer and a part-time analyst. Your job is to take that over, consolidate it into one trusted source of truth, govern it to HIPAA standards, and make it easy for the rest of the company to use. Our current data engineer will work alongside you during the handover. You will work directly with leaders in Clinical Operations, Finance, Marketing and Revenue Cycle Management. We are a small team, so we expect you to use AI coding agents every day to multiply your output.
What You’ll Own
Own the data infrastructure. Change data capture from our Cloud SQL databases into BigQuery, dataset permissions and data infrastructure on GCP, managed with Terraform.Own reporting for the whole company. Build and maintain Metabase dashboards and alerts, answer ad-hoc data requests from Clinical, Operations and Finance, and turn the questions people keep asking into standard reports.Run the data backlog. Take data requests through Linear, agree priorities with stakeholders and plan work ahead, so same-day requests are reserved for real incidents.Build and maintain ELT pipelines into BigQuery from our EHR (Healthie), customer support (Kustomer), marketing (Customer.io, Google Ads, Ours Privacy), product analytics (PostHog), and claims and billing (Candid Health).Model the business in dbt. Write clear, modular dbt models that encode the business logic for Finance, Clinical Operations, Marketing and Revenue Cycle reporting, including unit economics such as acquisition cost, lifetime value and cohort retention.Make the data trustworthy. Add tests, reconciliation checks and freshness alerts, and fix broken pipelines fast. Our data drives provider pay and billing checks, so correctness matters more than speed.Take over the systems we already run, including the provider pay pipeline, our verification-of-benefits accuracy model, marketing attribution and the Healthie data models.Connect our records. Match the same person across the EHR, support and marketing tools, and push computed attributes back into those tools (reverse ETL).Build a semantic layer so that both people (through Metabase) and AI agents can query our data with confidence.Govern PHI. Apply role-based and row-level access control, auditing and privacy controls across PHI and PII, in line with HIPAA.What We’re Looking For
5+ years in data engineering, with at least one role where you were the main or only data person.Expert SQL and strong Python. Production experience with BigQuery (or a similar cloud warehouse) and dbt.Experience building and running batch consumers for REST and GraphQL APIs.Hands-on experience with GCP and Terraform.Experience with healthcare data: handling PHI and PII and working within HIPAA requirements.You build reports and dashboards yourself, not just the pipelines behind them, and you are comfortable working with non-technical teams to find out what they actually need.You use AI coding agents (Claude Code, Codex or similar) in your daily work.Clear written communication. You can explain a data problem to a finance lead as easily as to an engineer.Nice to Have
Experience with EHR platforms (Healthie or similar).Experience with billing, claims or clearinghouse data (Candid Health or similar).Marketing attribution and acquisition funnel modeling.TypeScript.Kubernetes (GKE) or Cloud Run.Experiment design and statistical evaluation.Our Process
A short intro call.A take-home exercise, followed by a review session with our engineers.A working session with a product manager and someone from outside engineering.Compensation: $140,000 - $180,000 annually including above-market equity and benefits.
If you're interested in this role, please email hello@bircheshealth.com.
Compensation is determined by the applicant's education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.
