Data QA Engineer

Role Overview

Accountabilities

• Translate customer data extraction and web scraping requirements into testable criteria and QA strategies.
• Perform exploratory, manual, and visual testing, complemented by automated testing.
• Execute test cycles on extracted datasets to validate compliance and identify defects.
• Document defects with reproducible steps and supporting evidence.
• Apply descriptive statistics and visualizations to assess data quality and drift.
• Prepare quality reports and scoring metrics for internal teams and customers.
• Identify testing scope, untested areas, and associated risks.
• Collaborate with project managers and customers to clarify ambiguous requirements.
• Contribute to test automation frameworks emphasizing coverage, reliability, and performance.
• Improve QA processes and tooling including browser extensions and spreadsheet add-ons.
• Work independently while collaborating with QA leadership, developers, and project managers.

Requirements

• At least 5 years of experience as a QA Engineer or comparable role in 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 in at least one relational database environment.
• Strong understanding of HTML, XPath, JSON, HTTP, and CSS.
• Experience testing HTTP/REST APIs and validating responses.
• Solid knowledge of test case design, test data management, and exploratory and automated testing.
• Understanding of data quality principles including completeness, accuracy, consistency, and data drift.
• Experience in an Agile environment such as Scrum or Kanban.
• Familiarity with AI and LLM tools for test case generation and data validation.
• Proactive, detail-oriented mindset with strong ownership of project quality.
• Ability to learn new technologies quickly and adapt testing strategies.
• Strong written and spoken English communication skills.

Nice To Have

• Practical knowledge of Scrapy or other Python-based web scraping frameworks.
• Experience working with test automation frameworks.
• Interest in data science concepts applied to data analysis and validation.
• Enthusiasm for AI and LLM-powered approaches to data quality assurance.

Benefits

• 35 days of paid holidays.
• Flexible, location-independent working.
• Global, multicultural team.
• Modern open-source technologies and tools.
• Autonomy and ownership of QA processes and tooling.
• Collaborative environment with technical and project teams.

Compensation

• Salary, healthcare, retirement plans, and other benefits were not specified in the original job description.

Application Notes

• This position is listed on behalf of a partner company that manages all applications and next steps.
• Applications are reviewed via an AI-powered matching process before being shared with the hiring company.