Responsibilities

• Design, code, and execute automated test scripts to validate data integrity, completeness, and accuracy between source (Legacy/On-Prem) and target (AWS Cloud) systems.
• Analyze and test ETL/ELT pipelines using AWS Glue, Lambda, or Step Functions to ensure data transformation logic meets business requirements.
• Develop robust automated testing frameworks using Python and SQL to perform row counts, column mapping, and checksum validations on large datasets.
• Validate data ingestion and storage flows involving AWS services such as S3, Redshift, RDS, and DynamoDB.
• Utilize AWS Database Migration Service (DMS) and Schema Conversion Tool (SCT) to monitor replication tasks and identify discrepancies.
• Lead root cause analysis for data discrepancies, parse log files (CloudWatch), and work closely with Data Engineers to resolve ETL defects.
• Integrate data testing scripts into CI/CD pipelines (GitLab or Azure D...