AWS Test Engineer

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.