Manager, Energy Analytics

Meta's Infrastructure organization is seeking a Manager to lead energy analytics strategy for our global data center portfolio. As power demand grows by an order of magnitude over the coming years, energy cost and usage become increasingly material drivers of Meta's financial performance. In this role, you will lead a growing, geographically distributed team of experienced analysts responsible for developing the forecasting models and analytical frameworks that inform capacity planning, budgeting, procurement strategy, and rate design across Meta's data center infrastructure. As the portfolio continues to scale, this role carries increased ownership: setting standards across the team, developing experienced individual contributors and emerging leads, and serving as a primary energy analytics partner to Infrastructure and Finance leadership. You will also build the systems that quantify the portfolio's exposure to energy price and volume volatility across markets.

Responsibilities

Lead and grow a team of energy analysts spanning data center portfolio analytics, clean and renewable projects, cost and rate analysis, and load and generation forecasting. Own hiring, onboarding, capacity planning, and team structure as the function scales Develop ICs and emerging team leads; establish career pathways, calibration practices, and succession depth so the team's analytical capability is not concentrated in any single person Lead with accountability, transparency, and recognition, promoting continuous improvement and learning across the team Serve as an expert on energy rates and energy usage for Meta's growing global portfolio of data centers Own development and continuous improvement of models to forecast energy usage, generation, and cost, and to analyze electric rate impacts for current and future data center sites Set and enforce analytical standards across the team, covering methodology review, model documentation, version control, assumption governance, and QA of outputs used in financial and capacity decisions Support analysis and strategy for development of new rate structures for current and future data center locations, including in new and emerging markets Strengthen how the team characterizes uncertainty in its forecasts, moving beyond single point estimates toward ranges and scenario views that reflect price and volume variability, historical forecast error, and concentration by market, technology, and contract type Help establish and scale an energy risk quantification capability within Energy Operations, building the systems that measure Meta's exposure to energy price and volume volatility and partnering with Finance to define the analytics and reporting cadence that surface material exposure shifts early Build standardized tooling, data pipelines, and reporting that scale with the portfolio, reducing manual effort and streamlining communication of data and impact to the broader organization and leadership team Consolidate fragmented energy data across utility, market, and internal backend sources into durable, queryable data products with clear ownership Own the data controls and escalation paths that keep utility and market data reliable as transaction volume increases Lead development and delivery of monthly and annual summaries of key energy metrics to the Global Energy team, Infrastructure partners, Finance, and senior leadership Build strong partnerships with Infrastructure stakeholders to track data center design and capacity engineering trends, improve load forecasting methodologies, and support energy efficiency efforts; provide energy expertise to diverse internal teams and coordinate on relevant issues and requirements Represent energy analytics in cross-functional planning forums, translating analytical findings into clear recommendations and trade-offs for non-specialist audiences Refine processes, planning cycles, and reviews to support decision making, prioritization, and tracking of progress across key stakeholders Travel domestically and internationally as needed (up to 30%)

Qualifications

8+ years of relevant work experience with an electric utility, financial institution, energy supplier, renewable energy project developer, or energy-intensive consumer 4+ years of direct people management experience, including managing a team through growth and change Hands-on experience analyzing and interpreting energy usage data, electric tariffs, and wholesale energy market data Experience owning forecasting or analytical models used in budgeting, capacity, or investment decisions Experience building or materially scaling an analytical capability rather than inheriting an established one Advanced Excel skills and experience working with large data sets Communication and data visualization skills; experience developing narratives and communicating effectively with multiple stakeholders and leadership Experience training, mentoring, and leading analytics professionals, and experience developing team members at different points in their career Background establishing programmatic approaches to work, supporting teams, and developing cross-functional relationships Experience prioritizing across competing stakeholder demands and communicating trade-offs Experience with energy or commodity risk quantification: exposure measurement, probabilistic forecasting, scenario and stress analysis, or risk reporting Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience with Tableau or other data visualization software Experience overseeing a large energy portfolio including budgeting, forecasting, and data automation Experience managing a distributed or multi-site team, or managing managers/team leads Experience integrating AI tooling to redesign analytical workflows with measurable impact, including prompt and context engineering or agent orchestration, and developing models that bridge fragmented energy data across backend databases Experience with SQL and working directly with data warehouses or backend databases Experience with renewable energy procurement, PPAs, or clean energy project analytics Experience supporting large-scale infrastructure or data center growth Experience in international energy markets or regulatory environments Experience with Python programming