BI ETL Test Engineer
-
Capgemini
- Hyderabad
- Experienced Professionals
- Full Time
- FS
- Quality Engineering & Testing
Posted July 24, 2026 applications close August 23, 2026
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Job Description
Your Role
- Design and execute ETL test cases to validate data extraction, transformation, and loading processes across source and target systems.
- Develop and optimize complex SQL queries to perform data validation, reconciliation, and integrity checks in data warehouses and databases.
- Validate source-to-target mappings, transformation rules, data quality, and business logic to ensure accurate data movement and reporting. I
- dentify, analyze, and troubleshoot data discrepancies, ETL job failures, and performance issues, working closely with development and data engineering teams.
- Collaborate with Business Analysts, Developers, and QA teams to define test strategies, test scenarios, and acceptance criteria for data integration and warehouse projects.
Your Profile
- 6 to 9 years of experience in ETL and SQL Testing, with strong expertise in validating data warehouse and data integration solutions.
- Hands-on experience in ETL testing, including source-to-target validation, transformation testing, data migration, and data reconciliation.
- Strong proficiency in writing complex SQL queries for data validation, data quality checks, and backend database testing.
- Good understanding of Data Warehouse concepts, ETL architecture, dimensional modeling, and reporting/database systems
- Experience working in Agile/Scrum environments, collaborating closely with Data Engineers, Developers, Business Analysts, and QA teams.
What will you love working at Capgemini?
- Opportunity to work on large-scale ETL, Data Warehouse, and Data Migration projects across enterprise environments.
- Exposure to modern data integration technologies, cloud platforms, and advanced SQL-based testing frameworks.
- Structured learning programs, certifications, and continuous upskilling opportunities in ETL, Data Engineering, and Cloud technologies.
- Collaborative and innovation-driven culture focused on data quality, automation, and delivering reliable data solutions.