Data QA Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Data QA Engineer based in Mexico. As a Data QA Engineer, you will play a key role in ensuring the accuracy, completeness, and reliability of data delivered to customers. You will work with web data extraction projects and AI-assisted solutions, translating customer requirements into clear, measurable quality standards. Rather than treating quality assurance as a final checkpoint, you will help identify potential issues early and prevent defects before they reach production. Combining exploratory testing, data analysis, and automation, you will investigate anomalies and provide actionable insights to developers and project teams. You will use Python, SQL, and modern testing tools to assess data quality and communicate results through meaningful reports, metrics, and visualizations. Working closely with project managers, developers, and clients, you will have the autonomy to improve testing processes and strengthen quality practices. This is an opportunity to join a globally distributed, multicultural team that values ownership, continuous improvement, and flexible ways of working. Accountabilities: - Translate customer data extraction and web scraping requirements into clear, testable criteria and comprehensive QA strategies, taking ownership of quality assurance from the beginning of new projects. - Perform exploratory, manual, and visual testing, complemented by automated testing where it provides measurable value. - Execute test cycles on extracted datasets to validate compliance with customer specifications and identify inconsistencies, inaccuracies, missing information, and other defects. - Document defects clearly and thoroughly, providing reproducible steps and supporting evidence so developers can investigate and resolve issues efficiently. - Apply descriptive statistics, data summaries, and visualizations to assess completeness, accuracy, consistency, and data drift.

- Prepare quality reports and scoring metrics that communicate results honestly to internal teams and, where appropriate, customers. - Clearly identify the scope of testing, any untested areas, and the associated risks to support informed project decisions. - Collaborate with project managers and customers to clarify ambiguous requirements and ensure that expectations are measurable and testable before QA begins. - Contribute to the development and improvement of test automation frameworks, with an emphasis on coverage, reliability, and performance. - Identify, propose, and implement improvements to QA processes and tooling, including browser extensions, spreadsheet add-ons, and user-interface-based testing tools. - Work independently while maintaining close collaboration with QA leadership, developers, and project managers to uphold quality standards throughout delivery. Requirements: - At least 5 years of experience as a QA Engineer or in a comparable role involving software testing, data testing, or data quality assurance. - Proficiency in Python for data analysis and validation, preferably using Pandas and Jupyter notebooks. - Basic to intermediate SQL skills, including the ability to query and validate data in at least one relational database environment. - Strong understanding of web technologies and protocols, including HTML, XPath, JSON, and CSS. - Experience testing APIs and validating their responses against expected requirements. - Solid knowledge of test case design, test data management, and practical approaches to exploratory and automated testing. - Understanding of data quality principles, particularly completeness, accuracy, consistency, and data drift. - Experience working in an Agile environment, such as Scrum or Kanban, and collaborating effectively with developers.