Data QA Engineer
Jobgether (company site, opens in a new tab)5+ yrsRemoteDirect career pageEst. 8–14 LPA
Posted 14h ago
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Job description
Structured overview of role & requirements
About This Role
- Own QA from project kickoff for customer data-extraction and web-scraping work, turning requirements into measurable test strategies and validating dataset accuracy, completeness, consistency and reliability.
- Combine exploratory, manual, visual and automated testing with Python/SQL-based data analysis; investigate defects and assess anomalies or data drift.
- Report quality scores, coverage, limitations and risks to customers and internal stakeholders; improve test automation frameworks, tools and QA processes.
Minimum Requirements
- Work Experience Required: At least 5 years as a QA Engineer or in a comparable quality assurance role; software testing, data validation or data quality experience is preferred.
- Strong Python; basic-to-intermediate SQL with relational database experience; practical testing of HTTP/REST APIs; knowledge of HTML, XPath, JSON, HTTP and CSS.
- Experience with test planning, test design and execution, test data management, data-quality concepts, and Agile environments (Scrum or Kanban).
- India-based role; fully remote work is offered. Degree requirement and notice period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Best fit is an experienced QA professional who can own quality across data-extraction projects, from clarifying customer requirements to communicating release risks.
- Likely shortlist advantage for hands-on data analysis with Pandas/Jupyter, test automation framework experience, and familiarity with AI/LLM tools for QA; these are not all mandatory.
- Web-scraping exposure, including Scrapy or similar Python frameworks, aligns especially well with the project domain.