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Director, Advanced Manufacturing and Data Center Engineering
GoogleSão Paulo, State of São Paulo, BrazilSenior15+ years
Apply In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor’s degree in Engineering or Robotics and Automation Engineering Technology or or equivalent practical experience.
- 15 years of experience working within an industrial production environment.
- 15 years of experience working in manufacturing and with digital twins (virtual factory simulations tied to live production).
Preferred qualifications:
- Master’s degree in Mechanical/Industrial Engineering, Advanced and Intelligent Manufacturing, or in AI and Innovation.
- Experience leading structural transformations, including lifecycle integration or radical speed-to-market initiatives.
- Experience working with lean methodologies, Six Sigma, or similar industrial engineering principles applied to high-tech environments.
- Experience working in the end-to-end hardware lifecycle, from initial manufacturing through to automated provisioning and live serving.
- Experience with architecture of MES (Manufacturing Execution Systems), PLM (Product Lifecycle Management) and QMS (Quality Management Systems).
About the job
The SPO office is responsible for architecting, launching, and scaling a dual-focus partnership engine spanning both manufacturing and community ecosystems. The SPO organization will operate at the intersection of industrial innovation, external affairs, and civic impact, creating bridges between Google’s technology capabilities and the real-world partners.
As the Director of Advanced Manufacturing & Data Center Engineering, you will lead the next generation of our data center footprints. In this role, you will blend the precision and scalability of high-volume manufacturing with cutting-edge automation to optimize deployment, efficiency, and reliability. You will facilitate cross-functional engineering teams to design, productize, and automate physical infrastructure, treating the data center as a highly optimized "factory" for compute power. You will develop partnerships that will create leading edge automation solutions that are highly innovative, AI-integrative, and scalable across geographies and data center formats.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $256000 - $356000 (USD) + 30% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Apply advanced manufacturing principles (e.g., modular design-for-manufacturability, lean processes, robotics) to the deployment and scaling of data center infrastructure.
- Design and implement end-to-end hardware workflows, spanning automated hardware provisioning, robotics for asset tracking/migration, and automated cooling/power adjustments.
- Lead the evaluation and prototyping of emerging technologies (e.g., liquid cooling systems, next-gen power distribution units, AI-driven predictive maintenance).
- Leverage modeling & simulation to quickly assess design paraments against scale benefits.
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