QA lead

• 10 years of experience in data quality testing, with at least 5 years in a lead role.
• Hands-on experience with BigQuery, SQL, and Python for data validation and test automation.
• Strong understanding of ETL testing, data warehouse testing, and data lake validation.
• Experience with data testing frameworks
• Familiarity with cloud-based CI/CD tools and integrating test automation.
• Strong analytical and problem-solving skills for debugging data issues.

Test Strategy & Planning:
Develop and implement a data quality testing strategy covering data lake, data warehouse, and data pipelines.
Define test plans, test cases, and automation frameworks for data validation, transformation logic, and system integration
Establish best practices for data quality testing, anomaly detection, and root cause analysis.
Establish Entry & exit criteria and acceptance criteria for Functional testing
Establish plan & strategy for Performance testing

Test Execution & Automation:
Perform functional, regression, and performance testing of data pipelines and transformations.
Coordinate with & mentor Test Engineers / Data Quality Testers, Data Quality Analysts for successful Test execution.
Coordinate with offshore members (if any) for completion of Testing Life Cycle and adherence to Testing standards.
Automate data validation and reconciliation using Python, SQL, and testing frameworks.
Work with engineering teams to integrate automated tests into CI/CD pipelines for continuous testing.
Develop data comparison and anomaly detection scripts for large datasets in BigQuery.

Collaboration & Stakeholder Management:
Partner with data engineers, analysts, and business teams to define data quality requirements.
Work closely with DevOps to integrate data testing automation into deployment pipelines.
Lead data quality issue triaging, debugging, and resolution efforts.
Communicate data quality KPIs and test results to stakeholders.
Collaborate with UAT Testers as early in the life cycle.