- Key responsibilities:
1. 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.
2. 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.
3. 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.
4. 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.
• ct 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.