Data QA Engineer

About the role

We are seeking a Data QA Engineer to ensure the accuracy, completeness, and reliability of data delivered to customers. You will work on web data extraction projects and AI‑assisted solutions, translating customer requirements into measurable quality standards.

Key responsibilities

• Translate customer data extraction and web scraping requirements into testable criteria and comprehensive QA strategies.
• Perform exploratory, manual, visual, and automated testing of extracted datasets to validate compliance with specifications.
• Document defects with clear reproducible steps and supporting evidence for developers.
• Apply descriptive statistics, data summaries, and visualizations to assess data quality and drift.
• Prepare quality reports and scoring metrics for internal teams and customers.
• Collaborate with project managers, developers, and clients to clarify requirements and improve testing processes.

Required profile

• At least 5 years of experience in QA engineering, 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 for querying relational databases.
• Strong understanding of web technologies (HTML, XPath, JSON, HTTP, CSS) and experience testing REST APIs.
• Experience working in Agile environments and collaborating with developers.

Required skills

• Python
• Pandas
• Jupyter notebooks
• SQL
• HTML, XPath, JSON, HTTP, CSS
• REST API testing
• Test automation frameworks
• AI and large language model (LLM) tools (nice to have)
• Scrapy or other Python web‑scraping frameworks (nice to have)

What we offer

• 35 days of paid holidays.
• Flexible, location‑independent working.
• Globally distributed, multicultural team.
• Opportunity to work with modern open‑source technologies.
• Autonomy and ownership in shaping QA processes.