Analytics Engineer

What you will do

• Build canonical data models that create a shared source of truth across the company
• Define and maintain core business, operational, financial, product, and customer-facing metrics
• Model data in dbt or equivalent transformation tooling so dashboards, self-serve analytics, and customer reports pull from trusted tables
• Write tests, documentation, and data quality checks that catch issues before they reach users
• Create clear definitions for tables, fields, and metrics so teams understand what the data means and when to use it
• Reconcile metric definitions across internal teams, external reporting needs, and payer customer expectations
• Trace data lineage and debug dashboards, reports, or tables that change unexpectedly
• Partner with analysts, data scientists, operations, finance, product, engineering, and customer-facing teams to understand data needs and translate them into reliable models
• Help build reusable reporting frameworks that make onboarding new payers faster and less manual
• Partner with the data platform team to evolve warehouse tables, improve data architecture, and strengthen data contracts
• Improve warehouse cost, performance, and maintainability
• Support PHI-aware data access patterns and help ensure sensitive healthcare data is modeled and used responsibly

What you have done

• Built analytics engineering, business intelligence, or data modeling systems in a production cloud warehouse environment
• Written expert-level SQL and designed data models that support reporting, analysis, and decision-making
• Worked with dbt or an equivalent transformation framework
• Built tested, documented, reusable data models rather than one-off queries
• Defined, maintained, or reconciled business-critical metrics across teams
• Partnered with analysts, data scientists, operators, finance teams, product teams, or customer-facing stakeholders
• Debugged data quality issues, dashboard changes, metric discrepancies, and lineage problems
• Worked with cloud data warehouses such as BigQuery, Snowflake, Redshift, Databricks SQL, or similar
• Balanced speed, correctness, usability, and maintainability when building data assets
• Communicated clearly with technical and non-technical stakeholders about what data means and how it should be used

What gives you an edge

• Experience with healthcare data, claims data, EHR data, payer data, provider data, or other complex healthcare datasets
• Worked with PHI, HIPAA-aware data access patterns, or other sensitive regulated data
• Experience building customer-facing reporting, embedded analytics, or multi-tenant data models
• Worked with row-level security, access controls, or governed self-serve analytics
• Experience using Python for analysis, scripting, data validation, or automation
• Helped establish a semantic layer, metrics layer, or company-wide source of truth
• Built data models in a high-growth startup or operationally complex environment
• Experience improving warehouse performance, cost, and query efficiency

What makes you successful

• Treat a metric definition as a product artifact, not a Slack thread
• Make data trustworthy, reusable, and easy to understand
• Prevent metric chaos by building clear definitions, tests, and documentation
• Build so that a fix in one place does not require five copy-paste edits elsewhere
• Understand that internal users and external customers both need data they can trust
• Care about the usability of the data model, not just whether the pipeline runs
• Can explain data discrepancies clearly and drive teams toward shared definitions
• Build foundations that help the company move faster with more confidence

Day to Day

• Building or refactoring dbt models
• Adding tests to core tables
• Defining canonical fields and documenting how they should be used
• Reviewing metric definitions and reconciling them across teams
• Debugging a dashboard, report, or customer-facing metric that changed unexpectedly
• Tracing lineage from source systems through warehouse models to downstream reports
• Partnering with analysts, operators, finance, product, or customer-facing teams on reporting needs
• Improving warehouse performance, cost, and maintainability
• Designing reusable reporting structures that make new payer launches easier

What we offer

• Meaningful pre-IPO equity
• Medical, dental, and vision plans 100% paid for you and your dependents
• Flexible PTO + 10 paid holidays per year
• 401(k) with match
• 16-week parental leave policy for birthing parent, 8 weeks for all other parents
• HSA + FSA contributions
• Life insurance, plus short and long-term disability coverage
• Free daily lunch in-office
• Annual learning stipend
• Relocation assistance