Lead QA Engineer

Green Street Advisors - Newport Beach, CA

Full-time - Senior

Newport Beach, CA

Securities, Commodity Contracts, and Other Financial Investments and Related Activities

About the position

Green Street is seeking a skilled and hands-on Lead Data QA Engineer to join our technology team and ensure the highest quality for our data-driven products and analytics. The role involves close collaboration with the data engineering team to test complex, data-heavy applications in an Agile environment, supporting the mission to deliver world-class commercial real estate intelligence. The Lead Data QA Engineer will contribute to data quality practices and help build a robust and high-performing platform powered by best-in-class research, news, and data insights.

Responsibilities

• Collaborate with stakeholders and the technology team to ensure the timely and high-quality release of data-intensive applications.
• Drive process improvements, look critically at tooling and adjust as needed.
• Mentor other QA Engineers.
• Own the overall project QA lifecycle.
• Work with product and business teams to build and maintain detailed test plans with comprehensive data-focused test scenarios.
• Conduct story-level, regression, performance, and security testing as necessary to support platform releases.
• Validate and verify data quality, accuracy, and integrity across datasets, ensuring consistency in production environments.
• Manage test automation execution and help resolve or escalate issues affecting test outcomes.
• Contribute to improving test automation for data validation and advocate for data QA best practices to enhance efficiency.

Requirements

• 8-10 years as a QA Engineer in data-centric environments supporting data validation and quality for high-performance platforms.
• Experience managing teams of data QA engineers and driving common best practices, tooling decisions, and overall process improvements.
• Comfortable owning complete data QA projects and ensuring quality throughout the entire project testing lifecycle.
• Experience with scripting (Python or shell) for data validation automation.
• Advanced SQL skills must be able to write, analyze, and troubleshoot complex queries on SQL-based databases (MySQL, Oracle, etc.).
• Strong experience with data testing methodologies and practices, including working with large datasets and ensuring data consistency.
• Familiarity with test automation tools for data testing and experience using project management/ticketing systems like JIRA.
• Detail-oriented and quality-conscious, with a strong ability to work collaboratively and communicate effectively with engineering and business teams.

Nice-to-haves

• Familiarity with performance testing tools and knowledge of security testing practices.
• An understanding of tools used for data visualization and data interfaces.