ETL Testing

Cognizant

4 - 9 years

4 - 6 Lacs

chennai

Posted:2 hours ago| Platform: GlassDoor logo

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Skills Required

etl testing drive design test data extraction integrity sql report development resolve documentation efficiency regression reliability informatica talend analyze communication technology

Work Mode

On-site

Job Type

Part Time

Job Description

AIA – Face to Face Interview – Chennai

Skill: ETL Testing

Experience - 4 to 9 Years

Location: Chennai

Drive: 06 Dec 2025

Key responsibilities

Design and execution: Develop and execute test plans, test cases, and scripts to validate the entire ETL process, from data extraction to transformation to loading.
Data validation: Verify the accuracy, completeness, and integrity of data by comparing source and target data, often using SQL queries and ETL tools.
Defect management: Identify, document, and report defects and issues found during testing, and work with development teams to resolve them.
Collaboration: Work closely with ETL developers, data analysts, and business stakeholders to understand requirements and ensure the final data meets business needs.
Documentation: Maintain test cases, test scripts, and detailed documentation for testing procedures and results.
Automation: Develop and maintain automated test suites to improve efficiency, especially for regression testing.
Performance testing: Validate the performance and reliability of ETL operations to ensure they can handle the required data volumes.

Required skills and qualifications

Technical skills: Strong proficiency in SQL is essential for data validation. Knowledge of data warehousing concepts (like dimensional modeling) and various ETL tools (such as Informatica, Talend, or SSIS) is also required.
Analytical skills: Ability to analyze complex data sets and identify inconsistencies or discrepancies.
Communication skills: Effectively communicate test findings and potential solutions to both technical and non-technical audiences.
Problem-solving: Ability to troubleshoot and find the root cause of data quality issues.

Education: A bachelor's degree in computer science, information technology, or a related field is often preferred

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