Senior Manager, Data Engineering

What you'll do

• Design and operate data pipelines and analytic tables that feed the Medicare revenue projection model.
• Ingest, normalize, and reconcile claims, encounters, eligibility, EMR extracts, and CMS artifacts.
• Implement HCC/ICD-10 mapping and versioning to simplify data for modeling teams.
• Manage data quality, lineage, and snapshot processes required for financial accruals and audits.
• Maintain Databricks lakehouse standards including Spark/PySpark, orchestration, CI/CD, and access control.
• Define and monitor SLAs for data freshness, completeness, and source-system changes.
• Lead and mentor data engineers while establishing engineering practices for a regulated environment.
• Provide documented, trusted datasets to Finance, Actuarial, and Revenue Integrity teams.

What we're looking for

• Bachelor’s degree in Computer Science, engineering, or a related field (or equivalent experience).
• 8+ years of experience in data engineering.
• 4+ years of expert-level experience with healthcare data including claims, encounters, eligibility, provider, and clinical sources.
• 4+ years of hands-on production experience with Databricks/Spark (PySpark), Python, SQL, Lakehouse/ELT patterns, orchestration, and data-quality frameworks.
• 4+ years of experience supporting risk-adjustment, actuarial, or finance workloads involving reconciliation, point-in-time history, and auditability.
• Strong understanding of PHI, HIPAA, and controls for revenue and CMS-submission data.
• Familiarity with 834/837, ICD-10, and HCC assignment (preferred).
• Experience with SAS, direct RA files, or member-level RA engines (preferred).