Energy Analyst, New Transactions

Meta•Chicago, IL

2d•$132,000 - $188,000

About The Position

Meta designs, builds, and operates some of the most innovative and energy-intensive data centers in the world. As global demand for compute capacity grows, so does the complexity of securing reliable, cost-effective, and sustainable energy supply. Meta is seeking an experienced Energy Analyst to join the Infrastructure Data Center (IDC) Energy team, which is responsible for commercial energy strategy, rate analysis, and load forecasting across Meta's rapidly expanding data center portfolio. In this role, you will provide analytical expertise that directly informs site selection, energy procurement decisions, and long-term capacity planning.

Requirements

Bachelor's degree in a relevant technical field, finance, or business discipline, or equivalent practical experience
5+ years of relevant work experience in the energy industry, with a focus on analyzing rates and tariffs, market information, and load profiles to drive business decisions. This experience should preferably be with electric utilities, large energy consumers, energy service providers, or consultancies
Experience in analyzing electric utility tariffs, wholesale energy market data, load profiles, and renewable energy supply structures to support business decisions
Experience applying quantitative and financial modeling methodologies to evaluate energy market risks, rate scenarios, and cost optimization opportunities
Experience collaborating cross-functionally with Finance, Engineering, or Operations teams to translate analytical outputs into strategic recommendations
Experience building and maintaining scalable models or analytical tools to support energy forecasting and reporting workflows

Nice To Haves

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience working with electric utilities, independent power producers, energy service companies, or large-scale data center operators
Experience coding in Python, SQL, or similar languages to automate data processing and build analytical pipelines
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Proficiency with data visualization tools such as Tableau or equivalent platforms to communicate energy analytics to diverse audiences
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Familiarity with renewable energy procurement structures including power purchase agreements, renewable energy certificates, and virtual power purchase agreements

Responsibilities

Analyze electric utility rate structures, tariffs, and interconnection requirements for prospective and existing data center sites to support site selection and energy procurement decisions
Develop and maintain financial models to forecast energy consumption, evaluate rate scenarios, and quantify cost impacts across Meta's global data center portfolio
Conduct comprehensive load profile analysis and capacity planning studies to support infrastructure growth and energy agreement negotiations
Partner with Clean and Renewable Energy Managers to assess the financial and operational impact of renewable energy projects and power purchase agreements
Collaborate with Finance and Accounting teams to support deal evaluations, capital planning, and budget forecasting for energy expenditures
Engage with Infrastructure and Capacity Engineering stakeholders to incorporate data center design trends and hardware roadmaps into load forecasting methodologies
Build scalable analytical tools and dashboards to automate recurring energy reporting and streamline rate impact analysis
Synthesize wholesale energy market data, utility tariff filings, and regulatory developments into actionable insights for commercial energy strategy
Communicate complex energy concepts, tariff structures, and analytical findings clearly to cross-functional stakeholders including legal, real estate, and executive audiences
Identify opportunities to improve analytical frameworks and data pipelines in partnership with data engineering and data science teams