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Common QA title, metro location, but niche data QA skills reduce applicant density.
Core data QA and SQL skills transfer well across industries and tooling.
Several mandatory technical skills (SQL, data-warehouse testing, pipeline validation) but no strict years requirement.
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Own end-to-end quality assurance for data engineering projects including validation of data pipelines, completeness, and accuracy.
Write and execute SQL queries to test data quality across ETL/ELT workflows and perform smoke, regression, and integration testing post-deployment.
Support QA functions on web and app projects as needed and contribute to improving QA standards and documentation across teams.
Experience testing data pipelines, ETL, or data warehouse projects.
Strong SQL skills with ability to write complex queries for data validation independently.
Understanding of data warehousing concepts such as schemas, transformations, incremental loads, and slowly changing dimensions.
Experience with test management and defect tracking tools like Jira.
Comfortable working with large-scale data and capable of switching context across multiple projects and teams.
Ability to read and understand pipeline logic and data models to design meaningful tests and identify edge cases early.
Experience with Agile/Scrum methodologies and good communication skills to collaborate effectively across cross-functional teams.