Analytics Engineer
Own the semantic layer by building and maintaining core dbt data models that serve as the single source of truth for business metrics, dashboards, and reverse ETL pipelines in a HIPAA-compliant environment. First analytics hire at a fast-growing AI-native healthcare company.
About the job
What You'll Do
- Build and maintain the data models that define our core business metrics, from clinical outcomes to revenue to utilization, and own the sources of truth the whole company relies on.
- Run dbt orchestration with integrated alerting, CI/CD pipelines, and data quality testing that catches issues before they reach a dashboard.
- Stand up reverse ETL pipelines that feed clean, modeled data back into production systems, including population cohort definitions, marketing intelligence, and operational features.
- Implement and maintain access controls for PHI, keeping the data layer HIPAA-compliant while staying accessible to the people who need it.
What You'll Bring
- 3+ years of experience in analytics engineering, data analytics, or a hybrid data role.
- Deep expertise in SQL and dbt.
- Experience with BigQuery or comparable cloud data warehouses (Snowflake, Redshift).
- Experience working in a regulated industry (healthcare, fintech, insurance, government) with a proven ability to manage sensitive data and access controls; HIPAA familiarity a plus.
- Experience with data orchestration tooling (Paradigm, dbt Cloud, Airflow, or similar) and integrating analytics data back into production systems.
Who You Are
- Thinks in business entities and stakeholder questions, not just tables and joins, and turns fuzzy requirements into clean, well-modeled data.
- Treats dbt as a primary tool, writing clean, modular, well-tested transformations, with strong opinions about how a dbt project should be organized.
- Comfortable managing orchestration, environments, and reverse ETL pipelines without hand-holding, even without being a dedicated data engineer.
- Doesn't just model data, but asks why someone needs it and how it drives a patient or business outcome.
- Feels energized by creating structure in ambiguous, fast-moving environments, and can synthesize needs from multiple stakeholders into a clear data strategy.
What We Offer
- Competitive salary + equity.
- Comprehensive healthcare, vision + dental, 401K, Unlimited PTO, Parental Leave.
Skills
SQL, dbt, BigQuery, Snowflake, Redshift, Airflow, HIPAA, Reverse Etl, CI/CD, Data Modeling, Phi Access Controls
Similar jobs
Data Analytics jobs
Baseten
San Francisco, CA
The first dedicated marketing analytics hire will build the data foundation, measurement frameworks, dashboards, and experimentation capabilities connecting acquisition, product usage, and revenue. Requires 5+ years in marketing, growth, product analytics, data science, or another quantitative discipline, plus deep SQL and modern data-stack experience.
Eve
San Francisco, CAOwn growth and product analytics for activation, retention, expansion, and monetization, using experiments, SQL, AI automation, and product analytics tools. The role partners cross-functionally to turn insights into pricing improvements, product changes, and shipped growth initiatives.
Idme
Mountain View, CA
Analyzes and improves enterprise marketing systems, campaign data, automation workflows, and experimentation programs. The role requires 5–10 years of marketing systems experience, hands-on Marketo and Salesforce expertise, strong reporting and stakeholder-consultation skills, and a bachelor's degree or equivalent experience.
OnePay
United States
Own product and customer analytics across financial product experiences, turning behavioral data and customer feedback into roadmap recommendations and business decisions. The role requires 4–8 years of analytics experience, advanced SQL, strong analytical judgment, and daily fluency with AI-powered tools.
Discord
United States
Own fraud detection, payments operations, investigations, and risk strategy while leading cross-functional programs and launch assessments. The role requires 4+ years in payments, fraud, or risk operations, strong SQL and card-network expertise, and the ability to communicate decisions across technical and business teams.