Data Center Quality Engineering Manager
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Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Science or a related technical field equivalent practical experience.
- 10 years of experience in hardware quality engineering, manufacturing operations, or hyperscale data center environments.
- 3 years of experience managing technical teams of engineers or technicians in infrastructure.
- Experience using structured Root Cause Analysis (RCA) methodologies (e.g., 8D or 5-Why) to resolve hardware failures.
Preferred qualifications:
- Proficiency in quality improvement frameworks like Six Sigma, Lean, or ISO 9001 to manage hardware lifecycle standards.
- 10 years of experience in data center infrastructure or operation.
- Experience leading cross-functional problem-solving teams using practical approaches.
- Track record of coaching and mentoring technical teams, fostering a culture of continuous learning and data-driven decision-making.
- Ability to communicate complex technical findings into actionable executive summaries for cross-functional leadership and partner teams.
About the job
The mission of the Data Center Quality Engineering team is to identify and resolve product and process issues in the DC to ensure high quality deployments and reliable hardware that meet Google Cloud’s Time To Market (TTM) need. We exist in the data center to gather data, find root cause, and collaborate to create solutions that make our partner teams successful.
Responsibilities
- Provide expert-level technical direction for quality engineering, defining the goal across global regions and multiple data center product lines.
- Lead high-performing teams to optimize DC workflows, enhancing the speed and reliability of hardware deployments while eliminating systemic inefficiencies.
- Formalize feedback loops between field observations and product design to mitigate recurring hardware issues and evolve damage control programs.
- Own complex root cause analyses for critical, ambiguous technical issues, ensuring robust product quality and predictable fleet-wide deployment.
- Translate complex performance data and risk assessments into actionable strategic roadmaps and investment justifications for Director and VP-level leadership.
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