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.