Quality Engineering Lead – Data & Reporting Platforms
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Job Description
Structured overview of role & requirementsAbout This Role
Define and execute automated testing strategy for AI-powered data virtualization, federation, BI/reporting, and conversational AI query platforms.
Lead and manage a team of Quality Engineers, establishing standards, quality gates, and test automation maturity reporting to senior leadership.
Oversee end-to-end validation including data contract testing, security/access control testing, Big Data pipelines, and CI/CD integration to ensure secure, accurate, and performant data/report delivery.
Minimum Requirements
10-12 years in software testing, quality engineering, or data engineering.
5-8 years hands-on experience in automated data testing, ETL testing, or data pipeline quality engineering.
5-8 years experience in BI/reporting testing, data reconciliation, and source-to-target validation.
Bachelor’s degree in Computer Science, Information Systems, or equivalent engineering field.
Ideal Candidate Profile
Proven leader with experience managing specialized teams in Quality Engineering for complex, large-scale data and reporting platforms.
Technical expertise with data virtualization/federation platforms (e.g., Starburst, Trino), BI tools (e.g., Tableau), advanced SQL, Python/Java test automation, and CI/CD testing integration.
Experience designing multi-layered test strategies covering functional, integration, regression, and AI/NLP-driven query validation, preferably in agile environments.