Lead Data Quality Engineer - PA Locals - W2 Only

Position Title: Data QA Lead – Health Care Payer Domain
Location: Hybrid, PHL Area
Experience Level: 10 years

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.

Salary : $50 - $55