Staff Data Analytics Engineer
Staff Analytics Engineer owning the semantic layer and data models that serve as the single source of truth for dashboards, self-serve analytics, and AI agents on a Databricks/GCP platform. Requires 8+ years analytics/data engineering experience, deep SQL/Python, strong modeling skills, and production-grade data systems expertise.
About the job
Key Responsibilities
- Own the semantic layer: Design and maintain the metrics, dimensions, and data models that serve as the single source of truth across the business — built to be queried by humans and AI alike.
- Architect for AI-readiness: Structure our Databricks and GCP-based data platform so it can reliably power AI-driven analytics agents — clean schemas in Unity Catalog, consistent naming conventions, and strong data contracts.
- Drive data quality end-to-end: Build observability, testing, and alerting into pipelines so we catch problems before stakeholders do.
- Enable self-serve analytics: Partner with product, clinical, and business teams to deliver tooling and dashboards that let them answer their own questions without filing tickets.
- Set the standard: Establish and enforce data modeling conventions, documentation practices, and code review norms across the data org.
- Collaborate cross-functionally: Translate ambiguous business questions into data solutions; work with product engineering to improve event logging and measurement coverage.
Qualifications
- 8+ years of analytics engineering or data engineering experience, with clear progression to staff-level scope and impact.
- Deep SQL expertise and strong Python skills.
- Strong data modeling fundamentals — you know what clean, extensible, well-documented models look like and can build and enforce that standard regardless of tooling.
- Experience with modern data stack tools: Databricks, Snowflake or BigQuery, Airflow or similar orchestration, Looker/Tableau or equivalent BI tools.
- Track record of building resilient, monitored, production-grade data systems — not just pipelines that work, but ones that stay working.
- Strong communicator who can make technical tradeoffs legible to non-technical stakeholders.
- Bias toward action, entrepreneurial spirit, excellent communication, remote work adaptability, and commitment to continuous improvement.
Nice-to-Haves
- Experience with health tech or regulated data environments (HIPAA, PHI/PII handling).
- Familiarity with Databricks Unity Catalog, Delta Lake, or Spark.
- Experience building or integrating with AI/LLM-powered analytics tools or data agents.
- GCP experience.
Skills
SQL, Python, Data Modeling, Databricks, dbt, Snowflake, BigQuery, Airflow, Looker, Tableau, Unity Catalog, Delta Lake, Spark, GCP
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