1) Design and Develop Automated Data Quality Tests :
- Build reusable automated tests to validate data ingestion, transformations, and loading across Oracle, SQL Server, and Snowflake.
- Verify data integrity, completeness, schema conformity, and business logic through all layers from raw landing zone to curated data products.
2) Ensure End-to-End Data Pipeline Validation :
Automate testing for ETL / ELT processes, including data staging, cleansing, fact and dimension population, and final consumption layers.Monitor transformations and data flows across platforms (Oracle ? Snowflake, SQL Server ? Snowflake, etc.).3) Leverage Snowflake-Specific Testing Capabilities :
Utilize Snowflake's native SQL features (e.g., streams, tasks, time travel, variant types) in test development.Automate regression and functional testing for Snowflake data models, stored procedures, and materialized views.4) Build and Maintain a Cross-Platform Test Framework :
Extend or integrate automation frameworks compatible with Oracle, SQL Server, and Snowflake.Apply data validation tools to verify transformation accuracy.5) Utilize TestRail for Test Case Management :
Design, document, and maintain test cases and test plans in TestRail.Track execution, report defects, and ensure traceability across automated and manual test cases.6) Collaborate Across Data Engineering and Modeling Teams :
Work with data engineers, modelers, and analysts to define test criteria for ingestion jobs, business logic, and reporting outputs.Provide early feedback on development tickets and participate in code reviews.7) Support CI / CD and Test Automation in Production Pipelines :
Integrate automated tests into CI / CD workflows.Validate data integrity during production releases, schema updates, and Develop Monitoring and Alerting for Data Quality :Implement anomaly detection and alerting for critical pipelines (e.g., volume drops, schema drift, business rule violations).Create dashboards or automated reports for monitoring data quality trends.9) Ensure Test Coverage, Reusability, and Documentation :
Maintain reusable and version-controlled test suites across platforms.Document test strategies, data quality standards, and platform-specific :Bachelors or Masters degree in computer science, Data Engineering, or a related :3 to 5 years of experience in QA automation, with a strong focus on testing data pipelines, ETL / ELT processes, and data quality validation across platforms such as Oracle, SQL Server, and Snowflake.Proven experience in leading small teams or mentoring junior Skills :Strong expertise in QA practices for data platforms, including designing automated quality frameworks, validating data pipelines, and risk-based testing.Proficiency in automated testing strategies, TestRail for test management, Snowflake QA automation features, and scripting / CI / CD tools to maintain system accuracy and efficiency.(ref : hirist.tech)