Staff Data Analytics Engineer
RemoteUnited States
Job Summary
Own the semantic layer by designing and maintaining metrics, dimensions, and data models that serve as the single source of truth for dashboards, self-serve analytics, and AI-driven data agents. Architect the Databricks and GCP-based data platform to ensure reliable querying, enforcing clean schemas in Unity Catalog and strong data contracts. Drive end-to-end data quality by building observability, testing, and alerting into pipelines, while partnering with product and clinical teams to deliver tooling that empowers stakeholders to answer questions without filing tickets. Establish and enforce data modeling conventions, documentation practices, and code review norms across the organization. Translate ambiguous business questions into data solutions and collaborate cross-functionally to improve event logging and measurement coverage.
Required Qualifications
- 8+ years of analytics engineering or data engineering experience
- clear progression to staff-level scope and impact
- Deep SQL expertise
- strong Python skills
- Strong data modeling fundamentals
- Experience with dbt
- 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
- Strong communicator who can make technical tradeoffs legible to non-technical stakeholders
- Bias Toward Action: Demonstrated ability to take initiative, make decisions under uncertainty, and move projects forward even in the face of ambiguity
- Entrepreneurial Spirit: Strong adaptability to changing business needs with a knack for building and optimizing processes
- Communication: Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders
- Remote Work Adaptability: Comfort with remote work environments, demonstrating the ability to stay productive and connected with the team irrespective of physical location
- Continuous Improvement: A willingness to question assumptions and a commitment to continuous improvement
- 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
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