- Design and develop Python-based automation frameworks and reusable utilities for ETL validation and data reconciliation.
- Conduct end-to-end ETL testing, including source-to-target validation, transformation logic verification, and data completeness checks.
- Write, review, and optimize SQL queries (joins, CTEs, window functions) to validate complex business rules and data transformations.
- Execute Unix/Linux commands and shell scripts for ETL job monitoring, file validation, and log analysis.
- Work with Mainframe systems for flat file validation, dataset checks, and job executions in ETL processes.
- Test data warehouse components such as staging, fact, and dimension tables, including Slowly Changing Dimensions (SCDs).
- Integrate automated validation into ETL CI/CD pipelines (Jenkins, GitHub Actions).
- Collaborate with ETL developers, data modelers, and business analysts to investigate issues and ensure accurate data flow across banking systems.
- Prepare test evidence, automation reports, and dashboards for traceability and coverage metrics.