Data QA Lead – Health Care Payer Domain

About the Role

Seeking a Data QA Lead with strong experience in the healthcare payer domain to lead data quality assurance initiatives. The ideal candidate will have expertise in HEDIS, CMS Interoperability (FHIR), payer data standards, and hands-on experience with Azure Data Platform (Databricks, SQL, ADF pipelines). The focus is on ensuring data accuracy, reliability, and compliance while collaborating with data engineers, architects, and business stakeholders.

Key Responsibilities

Leadership & Strategy

• Define and own the Data QA strategy for enterprise data platforms. Ensure to covers functional, non-functional, integration, security and performance aspect.
• Lead and mentor a team of data QA analysts/testers across multiple projects.
• Establish data quality SLAs, metrics, and dashboards for business-critical datasets.

Data Testing & Validation

• Design and implement test plans, test cases, and test automation for data pipelines (ELT/ETL).
• Identify, log and track defects and issues using appropriate defect tracking tools. Provide detailed feedback to Engineering and Architecture teams to ensure efficient resolution.
• Validate payer data, including claims, membership, provider, and clinical datasets.
• Conduct FHIR-based API testing for CMS Interoperability compliance.
• Validate HEDIS measure calculations and quality reporting data.

Automation Strategy & Framework

• Define QA automation strategy for Databricks (Delta Live Tables, Delta constraints) and ADF pipelines.
• Implement reusable Great Expectations suites and integrate with CI/CD workflows.

Pipeline Quality Automation

• Embed DLT expectations and enforce Delta table constraints for schema and business rule validation.
• Automate ADF pre/post-copy checks, schema drift detection, and reconciliation logic.

CI/CD Integration

• Develop Azure DevOps pipelines with QA gates for Databricks Jobs/DLT, SQL Metadata and ADF deployments.

Technical Delivery

• Collaborate with Azure Data Factory (ADF), Databricks, and Snowflake engineering teams to ensure end-to-end data quality.
• Build and maintain data quality automation frameworks leveraging PySpark, SQL, and Python.
• Work with data governance and business teams to resolve data quality issues.

Performance & Scalability

• Design automated load and stress tests for large-scale data pipelines.

Compliance & Best Practices

• Ensure data QA practices adhere to HIPAA, CMS, and payer industry standards.
• Partner with data governance teams to validate data lineage and traceability.
• Document QA processes, test results, and provide audit-ready evidence.

Required Qualifications

Education:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.

Experience & Skills:

• 10+ years in data QA/testing, with at least 5 years in a lead role.
• Strong expertise in Azure Databricks (Delta Lake, Delta Live Tables, Unity Catalog).
• Hands-on experience with Azure Data Factory (pipelines, monitoring, CI/CD).
• Proficiency in Python, PySpark, SQL for test automation.
• Familiarity with Great Expectations, Azure DevOps, and Collibra.
• Knowledge of data governance, PII compliance, and data quality frameworks.
• Experience in CI/CD pipelines, DevOps practices, and cloud data platforms.
• Strong communication and leadership abilities for cross-functional teamwork.
• Experience with Agile/Scrum methodologies is plus.

Preferred Qualifications

• Experience with HL7/FHIR data models beyond payer use cases.
• Experience with Lakehouse architecture and medallion design patterns.
• Familiarity with BI tools (Power BI, Tableau) to validate reporting layer data.
• Understanding of data governance platforms (e.g., Collibra).
• Knowledge of automation frameworks for data QA and pipeline regression testing.
• Certifications: Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Data Engineer.