Technical Program Manager, Data Center Energy Risk Management
GoogleSan Francisco, California
Full-time
Salary
$138k–$197k/ annually
Free account to apply · application completed on Google
Salary
$138k–$197k/ annually
Free account to apply · application completed on Google
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
[https://www.google.com/about/careers/applications/benefits/].
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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