Key Responsibilities :

- Perform ETL testing, ensuring data completeness, correctness, and data quality across multiple sources.

- Validate Data Warehouse (DWH) transformations, business rules, and data mapping.

- Execute data testing including source-to-target (S2T) validation, reconciliation, and data profiling.

- Develop and maintain automation frameworks for ETL/DB testing using Python/SQL/Selenium/other tools.

- Conduct stress testing and performance testing for ETL pipelines, batch jobs, and BI reports.

- Validate cloud-based data solutions (AWS / Azure / GCP) including data flows, storage, and pipeline jobs.

- Work with Snowflake / BigQuery / Redshift / Azure Data Lake or similar data platforms.

- Collaborate with data engineers to debug issues and optimize data pipelines.

- Create detailed test plans, test cases, test scripts, and maintain documentation.

- Participate in Agile ceremonies and ensure quality delivery across sprints.

Technical Skills Required :

Core Testing Skills :

- ETL testing

- DWH testing

- Data validation & reconciliation

- SQL (advanced level)

- Automation testing for ETL/DB

Automation Tools / Technologies :

- Python / PyTest

- Selenium (if UI verifications needed)

- Informatica / Talend / DataStage (any ETL tool)

- Jenkins / Git (CI/CD)

Performance & Stress Testing :

- JMeter / LoadRunner / Locust

- Batch job performance validations

- Query optimization & execution tuning

Cloud Platforms :

- AWS (Glue, Redshift, S3, Athena)

- Azure (ADF, Databricks, Synapse)

- GCP (BigQuery, DataFlow)

- Cloud pipeline validation & performance checks

Soft Skills :

- Strong analytical & problem-solving abilities

- Excellent communication and documentation skills

- Ability to work with cross-functional teams

- Quick learner with strong debugging skills