Data QA Engineer

Description

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.

Role Overview

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.

Key Responsibilities

• 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.