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Job Description

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 migrations.


8) 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 practices


Education :


- Bachelors or Masters degree in computer science, Data Engineering, or a related field.


Experience :


- 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 engineers.


Technical 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.


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