What You’ll Do

• Data Quality Engineering: Develop, maintain, and automate data validation checks across claims, eligibility, EMR, and care management data.
• Reconciliation & Accuracy: Reconcile payer rosters, attribution files, and eligibility against claims and EMR data to ensure patient and cohort accuracy.
• Standards & Rule Definitions: Define quality rules for accuracy, completeness, timeliness, conformity, and uniqueness—mapped to business logic and regulatory requirements.
• Root Cause Analysis: Investigate data anomalies, ingestion failures, missingness patterns, mismatched identifiers, and lineage gaps; document root cause and corrective actions.
• Metadata & Lineage: Maintain source-to-target mapping, lineage documentation, and metric definition dictionaries with data engineering and analytics teams.
• Contract & Program Support: Ensure data meets quality thresholds for actuarial and contract performance use cases such as shared savings reconciliation and risk measurement.
• Provider & Payer Partnership: Collaborate with providers, payers, and vendors on file specifications, corrections, protocols, and reconciliation cadence.
• Data Onboarding & Integration: QA new data feeds (claims, eligibility, EMR extracts) to confirm conformity to specifications and downstream readiness.
• Governance & Controls: Contribute to data governance frameworks, access controls, and audit trails aligned with HIPAA, HITRUST, and internal standards.

Minimum Qualifications

• 3+ years in healthcare data quality, healthcare data operations, data engineering, or health informatics.
• Experience validating claims/eligibility (837/835 structures, CPT/HCPCS/ICD-10), NPI/taxonomy, and payer/provider data.
• SQL proficiency (joins, window functions, CTEs) and comfort with large relational datasets.
• Experience reconciling payer attribution and roster data with eligibility and claims.
• Understanding of value-based care concepts (attribution, TCOC, PMPM, risk adjustment, quality measures).
• Strong problem decomposition, documentation, and cross-team communication skills.

Preferred Qualifications

• Experience with HEDIS/STARS, RAF/HCC models, or other healthcare measurement frameworks.
• Familiarity with HL7/FHIR, CCD/CCDA, or EMR integration patterns.
• Python (pandas) or R for data validation scripting.
• Exposure to ETL/ELT tooling (dbt, ADF, SSIS, Informatica, etc.).
• Cloud data platforms (Azure Synapse/SQL, Databricks, Snowflake, Redshift).
• Experience contributing to or operating within data governance frameworks.

Tech Stack You May Use Here

• Data: SQL Server/Azure SQL/Synapse, Databricks, Snowflake, APIs/Flat Files
• Validation: SQL, Python (pandas), dbt (testing), Great Expectations (optional)
• BI (awareness): Power BI, Tableau
• DevOps: Git, CI/CD for data artifacts, lineage tools
• Standards: HIPAA, HITRUST, payer/provider file specifications