Roles & Responsibilities

ETL & Data Pipeline Testing

- Lead end-to-end testing of data pipelines, ETL workflows, and data transformation processes.
- Validate data movement across source, staging, and target systems.
- Perform source-to-target data validation and reconciliation testing.
- Verify business rules, transformation logic, aggregations, and data mappings.
- Ensure data accuracy, completeness, consistency, and integrity across systems.

AWS Glue & PySpark Testing

- Test and validate AWS Glue jobs, workflows, and ETL integrations.
- Validate PySpark-based data processing and transformation logic.
- Analyze job execution results and identify data discrepancies or defects.
- Support troubleshooting and root cause analysis for failed jobs and data issues.

Test Automation

- Design, develop, and implement automated testing solutions for ETL and data validation processes.
- Build reusable test automation frameworks and accelerators for lower environments.




- Develop automated reconciliation and source-to-target validation solutions using Python and PySpark.
- Enhance testing efficiency through automation and framework reuse across projects.

QA Strategy & Leadership

- Understand business requirements and translate them into comprehensive test scenarios and test cases.
- Identify testing risks, challenges, and quality gaps early in the project lifecycle.
- Define QA strategies, test plans, and validation approaches for complex data platforms.
- Drive defect management, test execution, and quality reporting activities.

Stakeholder Management

- Collaborate closely with onsite QA teams, developers, architects, and business stakeholders.
- Facilitate requirement discussions, issue resolution, and testing sign-offs.
- Provide regular status updates and communicate testing risks and dependencies effectively.

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📌 AWS Test Engineer (Pune)
🏢 Impetus Technologies
📍 Pune