This is a Contract to hire position.Position Summary
We are looking for an experienced Lead Data Quality Engineer to oversee data testing and quality assurance efforts within large-scale healthcare payer environments. The ideal candidate brings deep knowledge of payer data , HEDIS metrics , and CMS Interoperability (FHIR) , along with hands-on expertise across the Azure data ecosystem —including Databricks , SQL , and Azure Data Factory . This role focuses on building automated validation processes, ensuring compliance, and maintaining trust in enterprise data pipelines.
Core Responsibilities
Quality Leadership
- Develop and execute a data QA roadmap that covers all aspects of data testing—functional, non-functional, integration, and performance.
- Manage and mentor QA professionals working across data and analytics initiatives.
- Define measurable quality standards and dashboards to monitor key data assets.
Testing and Validation
- Design, automate, and maintain testing frameworks for complex data pipelines and ETL processes.
- Validate payer data elements, including claims, provider, and membership datasets.
- Perform API-level validation aligned with CMS FHIR interoperability standards.
- Verify HEDIS measure calculations and regulatory data submissions for accuracy.
Automation and Process Optimization
- Build reusable validation frameworks using PySpark , Python , and SQL .
- Implement automation checks in Databricks Delta Live Tables and ADF to detect schema drift, enforce data rules, and reconcile data movements.
- Integrate automated QA gates within CI / CD pipelines using Azure DevOps .
Collaboration and Technical Delivery
- Partner with data engineers, architects, and business analysts to resolve data integrity issues.
- Work with governance and compliance teams to align QA practices with HIPAA , CMS , and internal audit standards.
- Drive continuous improvement in testing efficiency and platform performance.
Required Skills and Experience
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 10+ years of experience in data QA / testing, with at least 5 years leading teams.
- Hands-on expertise with Azure Databricks (Delta Lake, DLT, Unity Catalog) and Azure Data Factory .
- Strong programming skills in Python , PySpark , and SQL for automation.
- Familiarity with Great Expectations , Azure DevOps , and data governance frameworks .
- Proven ability to manage QA across cloud-based data platforms using Agile / DevOps principles.
Preferred Skills
- Exposure to HL7 / FHIR data structures and payer interoperability standards.
- Understanding of Lakehouse and medallion architecture concepts.
- Knowledge of Power BI or Tableau for validating analytical / reporting layers.
- Experience with tools such as Collibra for data governance integration.
- Professional certifications such as Azure Data Engineer or Databricks Certified Engineer are advantageous.