Senior Data Engineer - Analytics

A senior analytics engineering position focused on turning messy operational healthcare data into trusted metrics that business leaders act on. The role is less about building pipelines and more about data modeling, measurement governance, and stakeholder-facing reporting across a unified analytics warehouse that spans multiple platforms and dozens of client workflows. Expect heavy time working alongside finance, operations, and client teams alongside deep hands-on work in dbt, SQL, and Power BI.

• Run discovery sessions with business stakeholders to translate ambiguous requests into acceptance criteria and testable definitions.
• Model noisy operational data into certified dimensional models using a Databricks bronze → silver → gold architecture in dbt and SQL.
• Own metric definitions end-to-end, consolidating redundant re-derivations into a single governed semantic layer.
• Build and maintain the Power BI semantic models, dashboards, and paginated reports, including refresh health and currency.
• Implement observability for models: freshness checks, statistical anomaly detection, value-drift monitoring, and CI-enforced regression guards.
• Design and own orchestration through dbt Cloud jobs and Airflow DAGs, ensuring dependable incremental runs and correct dependency ordering.
• Document work in design docs, model documentation, and handoff packets so successors can understand choices without re-deriving them.
• Codify recurring work into AI-assisted, testable workflows and supervise outputs from coding agents.

• 6+ years in analytics engineering, BI engineering, data engineering, or business analysis with production ownership of the models and metrics shipped.
• Expert SQL with strong dimensional modeling instincts and a reflex for spotting grain mismatches.
• Production dbt experience covering models, tests, macros, exposures, documentation, and CI.
• Hands‑on experience with a cloud lakehouse or warehouse;
  Databricks and Spark SQL preferred.
• Demonstrated BI ownership beyond underlying tables, with Power BI and DAX strongly preferred and Tableau, Looker/LookML, Metric Flow, or Cube as credible substitutes.
• Stakeholder fluency: run requirements conversations, frame data issues as business risk, and challenge incorrect metrics diplomatically.
• A reconciliation reflex, Git and pull‑request discipline, and comfort with high‑autonomy, async, Slack‑first environments.

• Healthcare data experience across claims formats (837/835/UB04), DRG/coding review, payment integrity, provider contracts, or revenue cycle.
• Data contracts, schema enforcement, ODCS‑style governance, or CI quality gating.
• Databricks Unity Catalog, lineage, and DBU cost accountability.
• Paginated reporting and Excel or SharePoint delivery for business‑formatted outputs.
• Pairing with AI coding agents and reviewing their output against a contract you wrote.

• US‑based remote work with a digital‑first operating model.
• Full medical, dental, and vision coverage for employees and their families.
• Unlimited flexible time off and a trust‑based, autonomy‑forward culture.
• Competitive salary with equity and 401(k) with employer match.
• Listed base pay range: $170,000 – $200,000, depending on experience and skills.