QA Leader - Data and Integrations
Description
Data Quality Strategy & Leadership:
- Define and execute a comprehensive data quality testing strategy for data products, data services, and integrations.
- Establish best practices for data validation, reconciliation, and anomaly detection.
- Develop data quality KPIs and metrics to measure and improve data reliability.
- Lead and mentor a team of data testers and QA engineers to drive excellence in data testing.
End-to-End Data Testing & Automation:
- Oversee functional, integration, regression, and performance testing of data pipelines and ETL processes.
- Implement automated data validation frameworks using Python, SQL, and cloud-native tools.
- Drive the integration of test automation into CI/CD/CT pipelines for continuous data quality assurance.
- Define and enforce data testing standards across teams to ensure consistency and accuracy.
Integration & Performance Testing:
- Lead data API and service integration testing to validate data flows between systems.
- Conduct performance and scalability testing to ensure the efficiency of data pipelines and queries.
- Collaborate with data engineers, architects, and DevOps teams to optimize data processing workflows.
Governance, Compliance & Issue Resolution:
- Ensure compliance with regulatory and security standards (e.g., HIPAA, GDPR etc).
- Establish and maintain data lineage, metadata validation, and data governance controls.
- Manage and drive resolution of data quality issues, defects, and anomalies through proactive monitoring.
- Act as a liaison between Product leaders, Delivery Leaders / Technical managers, End Users and QA Testers to ensure alignment on data quality goals.
Required Work Experience:
Lead and drive the end-to-end data quality strategy for our enterprise data products and services.
Required:
- 15+ years of experience in data quality testing, data validation, or data engineering QA, with at least 3+ years in a leadership role.
- Expertise in data warehouse, data lake, and ETL testing on cloud-based platforms (preferably GCP BigQuery).
- Strong proficiency in SQL and Python for data validation and automation.
- Experience with data testing frameworks (e.g., Great Expectations, dbt tests, Deequ).
- Proven track record of test automation, CI/CD integration, and performance testing.
- Defining Test Data requirements / Test Bed for large projects / programs
- Strong analytical and problem-solving skills with the ability to debug complex data issues.
- Excellent leadership, communication, and stakeholder management skills.
Preferred:
- Experience in healthcare data platforms and compliance regulations (HIPAA, FHIR, HL7).
- Familiarity with data observability, metadata management, and governance tools (e.g., Collibra, Monte Carlo).
- Knowledge of GCP data services, including Dataflow, Pub/Sub, and Cloud Storage.
- Experience in data API testing and service validation.