Advanced Analytics Engineer Senior
Novant Health · United States · US
Health Informatics
Remote
Not yet analysed
Demand82
Career growth78
Healthcare fit52
Remote potential90
5-year outlook
Senior healthcare analytics and data engineering roles are likely to remain competitive as health systems invest in cloud data platforms, governance, and analytics. Pay will vary by market, technical depth, and experience with Databricks, Power BI, and Epic data.
Clinical license
Not required
Applicant reach
narrow
Seniority
senior
Employment type
full-time
Date found
2026-10-30
Intelligence details
Flexible work details
- Engagement type
- Permanent
- Hours
- Full-time
- Eligible countries
- United States
- Rate period
- Annual
Listing via Himalayas.
Eligibility, licensing, and location restrictions can change. Always confirm details on the source posting before applying.
Why this is worth applying to
Worth considering only if you are a clinician with strong hands-on data engineering or analytics engineering experience, especially SQL, Python/PySpark, Databricks, and healthcare data. Most clinicians without a technical portfolio or prior BI/data warehouse experience should build those skills first.
Who should apply
Clinician-informaticists, clinical data analysts, healthcare data engineers, and Epic/Clarity/Caboodle-experienced professionals with strong SQL, Python, Spark, dimensional modeling, and cloud data platform skills. Physicians, nurses, pharmacists, or allied health professionals with a substantial analytics engineering portfolio may also be competitive.
CV angle
Frame your clinical domain knowledge as a bridge to translating healthcare requirements into data models, but lead with concrete data engineering deliverables: SQL/Python/PySpark pipelines, dimensional models, Databricks/Delta Lake work, Power BI optimization, CI/CD, data quality testing, governance, and PHI-safe handling. Highlight any Epic Clarity/Caboodle or healthcare analytics projects without overstating technical experience.
Skills to highlight
- SQL
- Python and PySpark
- Databricks and Delta Lake
- Dimensional modeling and data warehousing
- Power BI and analytics-ready datasets
- Azure DevOps, Git, and CI/CD
- Data quality, governance, and PHI/PII protection
- Epic Clarity/Caboodle and healthcare workflows
Role summary
A senior healthcare data engineering role focused on building scalable data products, dimensional models, curated data marts, and analytics assets in a cloud data platform. The engineer optimizes data for Power BI and advanced analytics, ensures data quality and governance, and collaborates with business and technical teams.
We publish our own intelligence summary, never the full job description. Always confirm details with the employer when you apply.