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Common senior QA title, metro location, broad SQL/ETL/automation requirements raise candidate competition.
Data/ETL testing skills transfer across industries but typically require analytics domain familiarity, so moderate sensitivity.
Mandatory SQL, ETL, data-validation, and automation skills increase filtering despite no explicit years requirement.
Define and implement comprehensive test strategies for data engineering and analytics projects, including test planning and risk mitigation.
Perform detailed test design and execution covering functional, integration, regression, data validation, and user acceptance testing.
Lead SQL-based data validation, ETL/data pipeline testing, defect management, automation of tests, and collaborate closely with stakeholders to ensure quality deliverables.
Proven experience with SQL, ETL/Data Pipeline Testing, Test Strategy & Planning, Data Analytics, and Automation Testing.
Experience in test case design, defect management, and stakeholder collaboration is mandatory.
Work Experience Required: Not explicitly mentioned in the JD.
Not explicitly mentioned: minimum educational qualification, notice period, or specific domain experience.
Experienced in defining and executing data validation and testing strategies in complex data engineering environments.
Capable of handling end-to-end test lifecycle including automation and continuous testing improvements for data pipelines.
Strong collaboration skills to work with business analysts, data engineers, product owners, and business users aligning testing outcomes with business needs.