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Lead Data QA
Lead Data QAe&e IT Consulting Services, Inc. • Philadelphia, PA, United States
Lead Data QA

Lead Data QA

e&e IT Consulting Services, Inc. • Philadelphia, PA, United States
[job_card.variable_days_ago]
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  • [job_card.full_time]
[job_card.job_description]

e&e is seeking a Lead Data QA for a hybrid contract opportunity in Philadelphia, PA!

The Lead Data QA is responsible for defining and driving the overall Data Quality Assurance strategy for enterprise-scale data platforms. This role ensures that all data systems meet rigorous standards for accuracy, performance, integration, security, and compliance. The Lead Data QA will provide leadership and mentorship to a team of data QA analysts and testers, establish quality frameworks for ETL / ELT pipelines, and integrate automation within Azure Data Factory (ADF), Databricks, and Snowflake environments. The ideal candidate possesses a deep understanding of data engineering, automation frameworks, and regulatory data compliance (HIPAA, CMS) within modern cloud architectures.

Responsibilities :

Leadership & Strategy

  • Define and own the enterprise Data QA strategy encompassing functional, non-functional, integration, and performance testing.
  • Lead and mentor a distributed team of Data QA professionals across multiple programs and data initiatives.
  • Establish and maintain data quality SLAs, KPIs, and dashboards for critical datasets.
  • Collaborate with data governance, engineering, and architecture teams to embed QA best practices across the data lifecycle.

Data Testing & Validation

  • Design and implement automated test plans, scripts, and frameworks for ELT / ETL pipelines.
  • Validate complex payer datasets including claims, membership, provider, and clinical data.
  • Conduct FHIR-based API testing for CMS interoperability and compliance standards.
  • Verify HEDIS measure calculations, healthcare quality metrics, and performance data accuracy.
  • Log and track defects using appropriate QA tools; provide detailed feedback to engineering and architecture teams.

    • Automation Strategy & Framework

  • Develop and implement a data QA automation framework for Databricks (Delta Live Tables, Delta constraints) and ADF pipelines.
  • Utilize Great Expectations for reusable validation suites integrated into CI / CD workflows.
  • Embed automated schema validation, reconciliation logic, and drift detection into data pipeline operations.

    • CI / CD Integration

  • Develop QA gates and automated quality checks within Azure DevOps pipelines for Databricks Jobs / DLT, SQL metadata, and ADF deployments.
  • Collaborate with DevOps and Engineering teams to embed QA automation into continuous integration and deployment processes.

    • Technical Delivery

  • Partner with ADF, Databricks, and Snowflake teams to ensure end-to-end data quality.
  • Build and maintain automation frameworks leveraging Python, PySpark, and SQL.
  • Participate in code reviews, data model validation, and regression testing across environments.
  • Work with business and data governance teams to identify, investigate, and remediate data quality issues.

    • Performance & Compliance

  • Design and execute automated load and stress tests for large-scale pipelines and dataflows.
  • Ensure all data QA processes align with HIPAA, CMS, and payer industry compliance standards.
  • Support audits through proper documentation of QA processes, test results, and lineage verification.

    • Requirements : Education :

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.

    • Experience & Skills :

  • 10+ years of experience in Data QA / Testing, with at least 5 years in a leadership capacity.
  • Strong proficiency with Azure Databricks (Delta Lake, Delta Live Tables, Unity Catalog).
  • Hands-on experience with Azure Data Factory pipelines, monitoring, and CI / CD deployment.
  • Advanced skills in Python, PySpark, and SQL for test automation.
  • Experience with Great Expectations, Azure DevOps, and data quality automation frameworks.
  • Familiarity with data governance, PII compliance, and enterprise data quality frameworks.
  • Proven success integrating QA practices into DevOps pipelines within cloud data environments.
  • Excellent communication, leadership, and cross-functional collaboration abilities.
  • Experience in Agile / Scrum environments is a plus.

    • Preferred Qualifications :

  • Experience with HL7 / FHIR data models beyond payer use cases.
  • Knowledge of Lakehouse and medallion architecture
  • Familiarity with BI validation using Power BI or Tableau.
  • Understanding of data governance platforms (e.g., Collibra).
  • Prior experience designing data QA automation frameworks for pipelines and regression testing.
  • Certifications such as Microsoft Certified : Azure Data Engineer Associate or Databricks Certified Data Engineer.
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