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Tier-1 brand, metro location, and broad mid-level data testing skillset drive high competition.
Specialized ETL, data warehousing, CDC and automation skills create high domain-specificity and low transferability.
Explicit 6-9 years plus mandatory ETL/data testing automation stack makes shortlisting stringent.
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Design, develop, and deploy automated test frameworks and solutions for ETL/ELT pipelines ensuring data accuracy, completeness, and integrity.
Execute database, file, and API level testing across structured and semi-structured data, including regression, integration, and system testing.
Analyze test failures, collaborate with data engineers to resolve issues, and maintain proper documentation for testing and production phases.
6-9 years of professional experience in ETL testing and automation.
Strong understanding of ETL concepts, data warehousing, data lakes, and UNIX environments.
Proficiency in automation tools: Python, PyTest, Robot Framework, or TestNG and advanced SQL (BigQuery preferred).
Degree required: B.E./B.Tech/MCA/M.E/M.Tech/MSc in Computer Science.
Experienced in designing and implementing automated testing frameworks specifically for complex data pipelines and ETL processes.
Familiar with modern data platforms such as Databricks, Snowflake, Redshift, Big Query, or Synapse and ETL tools like Informatica, Ab Initio, Talend, DataStage, or DBT.
Able to manage end-to-end testing processes, including planning, execution, defect reporting, and coordinating with process owners and data engineers to ensure quality and timely resolution.