Data QA Engineer - Remote

At Zyte, we eat data for breakfast and you can eat your breakfast anywhere and work for Zyte. Founded in 2010, we are a globally distributed team of over 250 Zytans working from over 28 countries who are on a mission to enable our customers to extract the data they need to continue to innovate and grow their businesses. We believe that all businesses deserve a smooth pathway to data.

Data QA is how we make sure the data we deliver is right before the customer sees it. As a Data QA Engineer, you will check the data our spiders and AI-assisted projects produce against what the customer asked for, find what is wrong and tell the team exactly what you found.

Quality assurance is more useful as a question asked at the start than a gate at the end. Is this requirement testable and how would we know if it were wrong? Part of this role is asking that question early, so problems are fixed before they reach the customer.

• Turn customer scraping and data requirements into a clear test approach and own QA from the start on new projects.
• Combine exploratory manual and visual testing with automated tests where automation pays for itself.
• Run test cycles on extracted data and report the results clearly.
• Write up defects with enough detail that a developer can reproduce and fix them without a conversation.
• Use descriptive statistics, summaries and charts to show how good the data is: completeness, accuracy, consistency and drift.
• Produce test reports and quality scores that give the team, and the customer where needed, a true picture.
• Say what was tested, what was not, and what risk that leaves.
• Work with project managers and clients to clear up unclear or untestable requirements before QA begins.
• Feed into our test automation framework, with a focus on coverage and performance.
• Suggest and take ownership of improvements to QA process and tooling, including browser add-ons, spreadsheet add-ons and UI-based test automation tools.
• Work with QA leadership, project managers and developers, with minimal supervision.

• 5+ years in a QA Engineer or similar role - testing software or data.
• Python preferred language - Pandas and Jupyter for data analysis and validation.
• SQL: basic to intermediate queries, and comfort with at least one relational database and its tools.
• A solid grasp of web technologies and protocols: HTML, XPath, JSON, HTTP and CSS.
• Experience writing tests against HTTP/REST APIs.
• Proactive and detail-oriented QA professional with a strong sense of ownership over project quality.
• Fast learner adept at rapidly understanding complex project domain requirements and adapting to new technologies.
• Leveraging AI and LLM tools to optimize test case generation and accelerate data validation processes.
• Good test case design and test data management.
• Experience working in an agile team (Scrum or Kanban) alongside developers.
• An understanding of data quality concepts such as completeness, accuracy, consistency and drift.
• Strong attention to detail, and the confidence to hold the quality line under delivery pressure.
• Clear written and spoken communication in English.

• Working knowledge of Scrapy and other Python-based scraping frameworks.
• Experience with test automation frameworks.
• Interest in data science concepts as they apply to data analysis and validation.
• Interest in using AI and LLM tools to speed up data validation.

Become part of a self-motivated, progressive, multi-cultural team.

Have the freedom and flexibility to work from where you do your best work.

Work with cutting-edge open source technologies and tools.

Originally posted on Himalayas