Technical Program Manager, Data Center Energy Risk Management

Socket.dev

New York (NY)

On-site

USD 138,000 - 197,000

Full time

13 days ago

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Benefits offered by this job

Equity
Benefits
Bonus target

Job summary

Google in the United States is seeking a Technical Program Manager to lead complex, multi-disciplinary projects focused on quantitative risk modeling and energy markets. You will work with stakeholders to plan requirements, identify risks, manage schedules, and communicate tradeoffs across executives and engineers.

The AI and Infrastructure team delivers AI capabilities and infrastructure at scale, empowering Google Cloud customers and billions of users.

Qualifications

  • Bachelor's degree in a technical or quantitative field or equivalent experience.
  • 2 years in technical program management with quantitative risk modeling, financial analysis, and data engineering.
  • Experience in energy sector, energy markets, or utility portfolio management.
  • Experience leading cross-functional programs with multiple dependencies across business and engineering teams.
  • Knowledge of energy risk management principles and quantitative analysis.

Responsibilities

  • Lead cross-functional technical programs bridging energy origination, finance, data science, and engineering to establish risk management frameworks.
  • Quantify and manage complex risk exposures across Google’s multi-gigawatt portfolio to support 24/7 carbon-free energy goals.
  • Partner with negotiators and engineers to develop programmatic evaluation tools for risk mitigation strategies.
  • Guide development of risk models and analytics platforms to evaluate clean energy investments and inform negotiations.
  • Synthesize market trends into long-term strategies while scaling automated, data-driven systems for portfolio risk-adjusted returns.

Skills

Technical program management
Quantitative risk modeling
Financial analysis
Cross-functional leadership
Energy market knowledge
Energy agreement structuring

Education

Bachelor's degree in technical or quantitative field
Master's degree in quantitative field

Tools

Python
SQL
C++

Job description

Minimum qualifications:
  • Bachelor's degree in a technical or quantitative field (e.g., Engineering, Mathematics, Computer Science), or equivalent practical experience.
  • 2 years of experience in technical program management, with a focus on quantitative risk modeling, financial analysis, and software or data engineering.
  • Experience in the energy sector, including wholesale power markets, renewable energy transactions, or utility portfolio management.
  • Experience managing technical initiatives and leading cross-functional programs with multiple dependencies across business and engineering teams.
  • Experience with energy agreement structuring, energy risk management principles, and quantitative analysis.
Preferred qualifications:
  • Master's degree in a quantitative field such as Mathematics, Statistics, Engineering, or a related discipline.
  • Deep expertise in major wholesale electricity markets (e.g., PJM, ERCOT, CAISO) and experience structuring complex transactions in multiple regions globally.
  • Proficiency in programming or query languages (e.g., Python, SQL, C++) to build, review, or scale advanced financial mathematics models, including option pricing, stochastic modeling, and monte carlo simulations.
  • Exceptional stakeholder management skills, with the ability to translate complex energy market dynamics into clear technical requirements for software engineers and strategic insights for leadership.
About the job:

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:
  • Lead cross-functional technical programs bridging energy origination, finance, data science, and engineering to establish comprehensive risk management frameworks.
  • Quantify and manage complex risk exposures across Google’s multi-gigawatt global portfolio to ensure alignment with 24/7 carbon-free energy goals.
  • Partner with negotiators and engineers to develop programmatic evaluation tools and guide transaction teams on optimal risk mitigation strategies.
  • Guide the technical development of risk models and analytics platforms to evaluate clean energy investments and inform commercial negotiations.
  • Synthesize market trends into long-term strategies while scaling automated, data-driven systems to optimize portfolio risk-adjusted returns and operational efficiency.
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