About the Role:
As a Lead ETL QA Engineer, you will drive the QA strategy and execution for a major data pipeline modernization initiative on Azure and Snowflake. This role requires a deep understanding of data quality frameworks, test planning, and stakeholder engagement. The candidate should possess leadership capabilities and be hands-on with SQL and automation.
The job responsibilities are as follows:
- Own QA strategy and execution for Azure-based data engineering projects.
- Define test plans and ensure traceability across test artifacts, requirements, and defects.
- Lead validation of Snowflake-based data lakes, transformations, and Power BI dashboards.
- Guide the QA team in testing complex SQL logic, Data Vault structures, and downstream integrations.
- Coordinate with product owners, architects, and developers to align test coverage with business logic.
- Manage test data setup, environment readiness, and pipeline triggers for testing in CI/CD workflows.
- Mentor junior team members and review their test deliverables for completeness and accuracy.
- Drive test automation initiatives using Python and Selenium, where applicable.
- Prepare quality metrics and test status reports for leadership and stakeholders.
Desired skills and experience
Must Have:
- 610 years of QA experience with strong exposure to Azure Data Factory pipelines.
- Expert in SQL, data profiling, complex joins, set operations, and anomaly detection.
- Experience validating Snowflake external/internal tables and pipeline integrations.
- Knowledge of Power BI reporting and back-end data validation.
- Experience in test management tools, Agile ceremonies, and client interaction.
- Ability to lead end-to-end test planning and delivery for large data programs.
Good to Have:
- Working knowledge of Data Vault modeling and related test patterns.
- Automation knowledge using Selenium with Python for data workflow and Business Logic validations.
- Familiarity with DevOps pipelines for test integration and execution.
