Description

Job Description:

  - Design and execute end-to-end test plans for ETL pipelines built on AWS Lambda, Step Functions, SQS, S3, and Airflow

  - Validate data transformations  confirm input JSON is correctly adapted and output matches expected schema

  - Write SQL test queries against Athena and Postgres to validate row counts, column values, and data completeness

  - Test cross-account data flows verify files land correctly, pipeline triggers fire, and status tracking updates as expected

  - Build reusable test data sets sample JSON files, mock S3 events, SQS messages

  - Perform negative testing  malformed files, missing fields, duplicate events, network failures

  - Validate DynamoDB state transitions PENDING IN_PROGRESS  COMPLETED / FAILED

  - Monitor CloudWatch logs during test runs and verify structured log output

  - Regression test existing Retirement pipeline after any new Connect changes

  - Document test cases, defects, and sign-off criteria per release

  - Coordinate UAT with business analysts  set up test data and validate reporting output in QuickSight / Athena

  - Hands on QTEST, QUMO

  Must Have

  - 3+ years ETL or data pipeline testing experience

  - Strong SQL  writing validation queries against large datasets, Athena or Postgres

  - AWS hands-on experience S3, Lambda, SQS, Step Functions, CloudWatch

  - Experience testing JSON-based data transformations  field-level validation, schema checks

  - Understanding of event-driven architectures  how S3 events, SQS, and triggers work end-to-end

  - Experience with test data management  creating, maintaining, and isolating test datasets

  - Ability to read Python code well enough to understand what a Lambda is doing  not necessarily write it

  - Strong defect documentation and test case writing and Qtest execution knowledge

Key Skills

Education

Any Graduate