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Open nowFirst seen 4 hours ago

Data Center Power Optimization Engineer

Google3,357 open roles

Where
Sunnyvale, CA, USA
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Your applicationOpen nowData Center Power Optimization EngineerGoogle · Sunnyvale, CA, USA

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 26 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.1%30 days
This job: first seen 4 hours ago

Google median: 26 days open

The posting

Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Power Engineering, a related technical field, or equivalent practical experience.
  • 10 years of experience in mission critical facility design and construction environments.
  • Experience working with cross-discipline teams (e.g., structural, civil, IT/Telecom, security, mechanical, or architectural).
  • Experience in people management and technical leadership.

Preferred qualifications:

  • Master's degree in Engineering, Business or other relevant field.
  • Professional Engineering (PE) license.
  • Experience in Estimating, Electrical design, Operation and Commissioning of substations, switchgear, ATP/ATS, emergency power systems and their control systems, power monitoring, and electrical protection.
  • Experience in design, construction, and commissioning of high voltage substations, medium or low voltage electrical distribution systems, AC/DC systems, and associated power management or SCADA tools.
  • Experience working with data center equipment/environments (e.g., switchgear, generators, transformers, controls, security monitoring systems, fire safety systems), with strong understanding of start up/commissioning processes.

About the job

Our thirst for technology is a part of everything we do. The Data Center Engineering team takes the physical design of our data centers into the future. Our lab mirrors a research and development department -- cutting-edge strategies are born, tested and tested again. Along with a team of great minds, you take on complex topics like how we use power or how to run state-of-the-art, environmentally-friendly facilities. You're a visionary who optimizes for efficiencies and never stops seeking improvements -- even small changes that can make a huge impact. You generate ideas, communicate recommendations to senior-level executives and drive implementation alongside facilities technicians.

With your technical expertise, you ensure compliance with codes and standards, develop infrastructure improvements and serve as an expert in your specialty (e.g., cooling, electrical).

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: $171000 - $247000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Research and develop new algorithms and methods for optimizing data center efficiency and performance. Design, validate, and implement controls algorithms to manage electrical and mechanical stability.
  • Analyze and recommend approaches to manage dynamics of the electromechanical systems and their interactions within a data center.
  • Conduct empirical statistical analysis/modeling on relevant data for use in data center controls.
  • Optimize the entire data center system, with a view across data center architecture, electrical, cooling, and power management.
  • Collaborate with the Engineering team to implement proposed strategies and algorithms in our technology system; develop Machine Learning algorithms for pattern recognition and Bayesian and non-linear systems.
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