Senior Manager, Data Engineering — Medicare Revenue

CVS Health•Washington, NV

5d•$82,940 - $182,549

About The Position

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. This role owns the data foundation that the Medicare revenue engine runs on. It requires an expert in healthcare and risk-adjustment data, including claims, encounters, eligibility, clinical/chart sources, and CMS payment and diagnosis files. Expertise in production-grade platforms (Databricks / Spark lakehouse, Python, SQL) is also required. The job is to make member-month, diagnosis, and payment data timely, complete, lineage-traced, and auditable so Finance can forecast and book revenue with confidence.

Requirements

8+ years in data engineering
4+ years of expert level experience in healthcare data: claims, encounters, eligibility, provider, and clinical/chart sources ;
4+ years of hands-on production experience with Databricks / Spark (PySpark), Python, and SQL/ Lakehouse / ELT patterns, orchestration (e.g., Airflow or equivalent), and data-quality frameworks.
4+ years of experience supporting risk-adjustment, actuarial, or finance workloads (reconciliation, point-in-time history, auditability).
Strong understanding of PHI, HIPAA, and controls appropriate to revenue and CMS-submission data.

Nice To Haves

Familiarity with 834/837, ICD-10, and HCC assignment.
SAS (nice to have, especially for legacy actuarial extracts).
Direct RA file experience (MMR, MOR, MAO-004, EDS/encounter status).
Prior work on member-level RA engines, suspect/recapture warehouses, or revenue-forecast data products.

Responsibilities

Design, build, and operate the data pipelines and analytic tables that feed the Medicare revenue projection model (member-month grain, HCC/diagnosis history, engagement/visit flags, CMS files, program attributes).
Ingest, normalize, and reconcile: claims/encounters (837 and internal), eligibility/enrollment, EMR/chart extracts, vendor/program files, and CMS artifacts (MMR, MOR, MAO-004, and related).
Implement HCC / ICD-10 mapping, model-year (e.g., V24/V28) versioning, and diagnosis-year vs. payment-year constructs so modelers do not have to reverse-engineer source systems.
Own data quality, reconciliation, lineage, and snapshot/freeze processes required for accruals, AtoE, and audit.
Partner with enterprise data/IT on Databricks (or equivalent) lakehouse standards: Spark/PySpark, orchestration, CI/CD, access control, and cost/performance.
Provide trusted, documented datasets to Modeling, Finance, Actuarial, and (as needed) Revenue Integrity.
Define SLAs for freshness and completeness; monitor drift and source-system changes that would invalidate forecasts.
Lead and mentor data engineers; set engineering practices for a regulated, financially sensitive environment.
Support modular outputs (revenue, membership/mix, other items) so the engine can evolve without rewriting the warehouse.