Job Summary :

We are looking for an experienced ETL Test Engineer with strong expertise in data validation, ETL testing, and data warehousing concepts. The ideal candidate should have hands-on experience in validating complex ETL workflows, writing advanced SQL queries, automating data validation processes, and ensuring data quality across enterprise data platforms. The role requires close collaboration with data engineering, analytics, and business teams to deliver high-quality, reliable data solutions.

Key Responsibilities :

- Analyze business and functional requirements to develop comprehensive ETL testing strategies and test plans.

- Design, develop, and execute test cases for ETL workflows, data migration, and data integration processes.

- Perform source-to-target data validation to ensure data accuracy, completeness, and consistency.

- Validate complex data transformations, business rules, and aggregation logic.

- Execute functional, integration, regression, and end-to-end testing for ETL pipelines.

- Develop and maintain automated data validation scripts using SQL, Python, or Shell scripting.

- Perform ETL job performance testing and identify opportunities to optimize data processing efficiency.

- Identify, document, track, and verify defects using defect management tools.

- Collaborate with Data Engineers, Developers, Business Analysts, and QA teams to resolve data quality issues.

- Prepare test execution reports, defect summaries, and quality metrics.

- Ensure compliance with data governance, quality standards, and testing best practices.

Required Technical Skills :

- 5-10 years of experience in ETL Testing, Data Warehouse Testing, or Data Validation.

- Strong expertise in writing complex SQL queries for data validation and reconciliation.

- Hands-on experience with one or more ETL tools such as :

1. Informatica PowerCenter

2. Talend

3. Microsoft SSIS

4. IBM DataStage

5. Ab Initio (preferred)

- Strong understanding of ETL workflows, data integration, and data migration processes.

- Solid knowledge of Data Warehousing concepts including Facts, Dimensions, Star Schema, and Snowflake Schema.

- Experience with relational databases such as Oracle, SQL Server, PostgreSQL, MySQL, or Teradata.

- Hands-on experience in regression, integration, and end-to-end testing of data pipelines.