Lead Software Test Automation Engineer

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We are hiring a QA Lead to drive the quality strategy and leadership across a multi-layered analytics ecosystem (Data and AI) that powers enterprise decision-making. This role is ideal for someone who combines strategic thinking, cross-functional leadership, and a solid understanding of data platform operations.

This is a leadership-first role, with a strong focus on quality governance, and cross-team alignment. While the primary emphasis is on leading and shaping quality practices, a solid technical foundation is essential. Particularly in understanding data platforms and live systems, to effectively guide the team, make informed decisions, and uphold quality standards.

Responsibilities:

• Define and own the QA strategy for the analytics ecosystem, ensuring alignment with business goals and engineering priorities.
• Lead and mentor QA engineers, fostering a culture of quality ownership, collaboration, and continuous improvement.
• Ensure QA practices are aligned with the company-wide standards, contributing to guild initiatives and helping evolve shared best practices.
• Establish and monitor quality KPIs across data, BI, and web layers, including data accuracy, system performance, and release readiness.
• Partner with engineering, product, and data teams to embed quality early in the development lifecycle.
• Drive risk assessment, release governance, and production validation processes.
• Guide automation efforts and CI/CD integration
• Support troubleshooting and root cause analysis for production issues, with a focus on data accuracy and system stability
• Hands-on in critical areas, actively contributing to test design, data validation, and production monitoring to ensure quality is upheld in live environments

Knowledge, Skills, Abilities:

• Proven experience leading QA efforts in data-centric or analytics-driven environments.
• Ability to define and execute QA strategies, including test planning, risk management, and release readiness.
• Excellent communication, stakeholder management, and leadership skills.
• Strong experience in mentoring and developing QA engineers, fostering a culture of ownership, accountability, and continuous improvement.
• Skilled in cross-functional collaboration, working closely with engineering, product, and data teams to embed quality throughout the development lifecycle.
• Experience working in Agile environments, including Scrum and SAFe frameworks.
• Understanding of data platforms, ETL/ELT processes, and data quality principles.
• Familiarity with Python and SQL for data validation and automation.
• Experience with Microsoft Azure data services (Data Lake, Data Factory, etc.).