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Metro mid-level data QA role with broad skill requirements and moderate employer brand.
Highly domain-specific ETL, DWH testing and SQL requirements limit cross-industry transferability.
Explicit 6+ years plus specific ETL/DWH/automation and SQL requirements increases filter strictness.
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Design and execute test cases to validate ETL flows, data transformations, aggregations, and data reconciliation for data projects.
Maintain regression test suites and perform testing on data processing workflows to ensure data accuracy, completeness, and reliability.
Collaborate with data engineering, analytics teams, and other stakeholders to identify and resolve data quality issues and support User Acceptance Testing and defect management.
6+ years of experience in ETL testing, data warehouse (DWH) testing, and automation testing.
Strong proficiency in advanced SQL queries and test management tools.
Experience with AI Agents and Machine Learning (MLOps/L-Ops) frameworks in testing contexts.
Working knowledge of data processing technologies, testing methodologies (manual, API, automated), CI/CD processes, and cloud environments.
Experienced in complex data quality issue analysis and resolution with multi-angle problem solving approach.
Comfortable collaborating effectively with cross-functional teams including data engineers, analysts, and product teams.
Familiar with data governance and compliance standards relevant to large-scale data projects.