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Mid-level Bengaluru automation role with common QA skills creates moderate applicant competition.
Data QA automation and SQL skills are fairly transferable across industries with ETL and API testing needs.
Requires specific automation, SQL, and CI/CD skills but no explicit years, so filters are moderately strict.
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Own the automation of data quality validation for customer-facing analytics platforms, including API and web automation frameworks.
Identify, scope, and resolve data quality issues through automated testing of ETL pipelines, data transformations, and business rules across large datasets.
Integrate automated validation and quality gates into CI/CD pipelines and contribute to the evolution towards full-stack and AI-driven engineering modules.
Strong hands-on coding skills in JavaScript or Python, with capability to handle full-stack code including React and API development.
Experience developing and maintaining automated testing frameworks (e.g., Cypress, Playwright, Selenium).
Advanced SQL skills for database validation, reconciliation, and integrity checks.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced engineer focused on automation-first approaches to data quality in high-volume, complex data environments.
Comfortable working with API/web automation and integrating AI technologies to enhance automated testing coverage and anomaly detection.
Able to expand skillset towards full-stack and AI-driven development, demonstrating adaptability and technical growth within a product engineering team.