Data QA Engineer

Accountabilities: Translate customer data extraction and web scraping requirements into clear, measurable testing strategies, taking ownership of quality assurance from the beginning of new projects. Design and execute comprehensive test plans combining exploratory, manual, visual, and automated testing approaches according to project needs. Perform regular testing cycles on extracted datasets to validate data accuracy, completeness, consistency, and reliability. Identify, investigate, document, and report defects with clear reproduction steps and sufficient technical detail to enable developers to resolve issues efficiently. Apply descriptive statistics, data summaries, and visualizations to assess data quality, identify anomalies, and monitor potential data drift. Prepare detailed test reports and quality scores, providing internal stakeholders and customers with an accurate understanding of project quality and potential risks. Clearly communicate testing coverage, limitations, unresolved issues, and remaining risks throughout the delivery process. Collaborate with project managers and customers to clarify requirements, identify ambiguities, and ensure that expectations are measurable and testable before QA activities begin. Contribute to the development and continuous improvement of test automation frameworks, focusing on test coverage, reliability, and performance. Identify and implement improvements to QA processes and tools, including browser extensions, spreadsheet add-ons, and user-interface-based testing solutions. Work closely with QA leadership, developers, and project managers to maintain high-quality standards while operating with a high degree of independence. Requirements: At least 5 years of professional experience as a QA Engineer or in a comparable quality assurance role, preferably involving software testing, data validation, or data quality. Strong Python programming skills, ideally with practical experience using Pandas and Jupyter Notebook for data analysis, processing, and validation. Basic to intermediate SQL knowledge, with the ability to write queries and work confidently with at least one relational database and its associated tools. Solid understanding of web technologies and protocols, including HTML, XPath, JSON, HTTP, and CSS. Practical experience designing and executing tests for HTTP and REST APIs. Strong knowledge of test case design, test planning, test execution, and test data management. Understanding of key data quality concepts, including completeness, accuracy, consistency, reliability, and data drift. Experience working in Agile development environments, including Scrum or Kanban, and collaborating closely with software developers. Familiarity with AI and Large Language Model (LLM) tools, particularly their application in generating test cases, accelerating data validation, and improving QA workflows. Excellent analytical and problem-solving abilities, combined with strong attention to detail and a proactive approach to quality ownership. Ability to quickly understand complex project requirements, learn new technologies, and adapt to changing priorities. Confidence in maintaining high-quality standards and raising concerns when delivery timelines or project pressures could compromise quality. Excellent written and verbal communication skills in English. Nice to Have: Working knowledge of Scrapy and other Python-based web scraping frameworks. Previous experience developing or working with test automation frameworks. Interest or experience in data science concepts, particularly as applied to data analysis, interpretation, and validation. Enthusiasm for exploring AI and LLM-powered tools to improve testing efficiency and accelerate data quality assessments. Benefits: Fully Remote Work: Enjoy the freedom and flexibility to work from anywhere in the world, choosing the environment where you are most productive. Generous Paid Leave: Benefit from 35 days of paid holidays per year, supporting a healthy work-life balance. International Team: Become part of a self-motivated, progressive, and multicultural team of more than 250 professionals distributed across over 28 countries. Innovative Technologies: Work with cutting-edge open-source technologies, modern tools, and innovative data extraction solutions. Flexible Working Environment: Enjoy the autonomy and flexibility to organize your work in a way that supports productivity and personal wellbeing. Professional Growth: Develop your technical expertise by working on challenging data quality projects alongside experienced professionals in a collaborative environment.