Job Summary
We are looking for an experienced ETL / BI Automation Tester to validate data pipelines, data warehouses, and BI reports. The ideal candidate will have strong experience in ETL testing, data validation, SQL, and automation testing, ensuring data accuracy, completeness, and performance across complex data systems.
Key Responsibilities
- Design and execute ETL and Data Warehouse test cases for source‑to‑target data validation
- Perform data reconciliation, data quality, and data integrity testing
- Automate ETL/BI test scenarios using automation frameworks and scripting
- Validate BI reports, dashboards, and KPIs against backend data
- Perform SQL-based data analysis to verify transformations and aggregations
- Execute regression, system, and integration testing for data pipelines
- Test batch jobs, workflows, and scheduling processes
- Perform performance and volume testing for large datasets
- Identify, log, and track defects using tools such as JIRA
- Collaborate with Data Engineers, BI Developers, and Business Analysts
- Prepare test plans, test cases, test execution reports, and defect metrics
Mandatory Skills
ETL / Data Testing
- Strong experience in ETL Testing / Data Warehouse Testing
- Hands‑on with ETL tools (any of the following): Informatica / Talend / DataStage / SSIS / Databricks
- Source‑to‑Target (S2T) mapping validation
SQL & Databases
- Excellent SQL skills (complex joins, sub‑queries, aggregations)
- Experience with databases: Oracle / SQL Server / MySQL / PostgreSQL
- Cloud DWH: Snowflake / Redshift / BigQuery
Automation Testing
- Experience with test automation using:
- Python / Java
- PyTest / TestNG / Selenium (for BI UI where applicable)
- Knowledge of CI/CD integration for test automation
BI / Reporting
- Experience testing BI tools:
- Power BI / Tableau / MicroStrategy / Qlik
- Validation of dashboards, reports, and data visualizations
Good to Have Skills
- Experience in Cloud platforms (AWS / Azure / GCP)
- Knowledge of Big Data technologies (Hadoop, Spark)
- Experience in banking, insurance, or financial services domain
- Understanding of data governance and data quality frameworks
- Exposure to Agile/Scrum methodology
- Experience in Risk domain and Moody's (Moody's Risk, Credit Risk, Regulatory / Risk data) testing
