Quality Analyst, Data Solutions & Initiatives

What you'll do

• Define and implement test strategies based on functional requirements for new developments and regular data loads.
• Validate the quality, reliability, and correctness of AI-powered and LLM-based features in production scenarios.
• Execute repeatable test scenarios to enable consistent data quality monitoring across source systems and reporting environments.
• Coordinate release management and provide the final go/no-go decision regarding data quality and functional behavior.
• Act as the first gate for production issues by confirming behavior and determining priority with product managers.
• Manage tickets for data issues and collaborate with product managers to plan and prioritize bug fixes.
• Report data findings and status updates to stakeholders in a clear, structured, and actionable manner.

What we're looking for

• At least 5+ years of relevant experience in QA, Quality Engineering, Data QA, or a similar field.
• Bachelor’s degree in Computer Science, Engineering, or Information Systems, or equivalent practical experience.
• Experience applying a data-driven QA approach, including data reconciliation or validation, in business-critical environments.
• Experience with automated test framework design or test infrastructure beyond individual test case execution.
• Hands-on experience with SQL and at least one analytics or reporting tool to independently investigate and validate datasets.
• Experience executing automated test cases using languages or frameworks such as Python, JavaScript, or Selenium.
• Experience working in cross-functional teams using Agile frameworks such as Scrum or Kanban.
• Familiarity with LLM-based or AI-powered systems, including prompt-based systems and understanding how inputs affect outputs.
• Experience validating backend APIs, data pipelines, or service-based systems (preferred).
• Strong proficiency in SQL, including complex joins, aggregations, and large dataset validation (preferred).
• Understanding of dimensional modeling, data warehousing, and testing data migration projects (preferred).
• Familiarity with CI/CD pipelines and experience with observability, logging, or monitoring for data or AI systems (preferred).
• Domain experience in BI, financial, or hierarchical data systems (preferred).
• Master’s degree (preferred).