Portfolio Strategy Analyst, Data Center Energy

Meta Meta · Big Tech · Austin, TX +2

This role focuses on developing and maintaining portfolio-level energy strategy models for data centers, analyzing energy markets, and synthesizing data to inform infrastructure leadership. It involves identifying strategic risks and opportunities related to energy, partnering with other teams, and building analytical tools. The role requires experience in energy strategy, financial modeling, and energy markets, with a demonstrated ability to integrate AI tools to optimize workflows and develop AI skills.

What you'd actually do

  1. Develop and maintain portfolio-level energy strategy models that assess capital and operational cost implications of data center development decisions across multiple geographies
  2. Analyze energy market structures, utility rate environments, and grid interconnection timelines to inform site selection and development sequencing decisions
  3. Synthesize load forecasting data, capacity planning inputs, and energy procurement signals to produce integrated portfolio outlooks for infrastructure leadership
  4. Identify strategic risks and opportunities across the data center development pipeline related to energy availability, grid constraints, and regulatory changes
  5. Partner with Commercial Energy and Clean Energy teams to align the energy strategy with broader infrastructure development priorities

Skills

Required

  • Energy strategy
  • Infrastructure development
  • Portfolio planning
  • Financial modeling
  • Market analysis
  • Energy markets
  • Data analysis
  • SQL
  • Python

Nice to have

  • AI tools integration
  • AI skill development
  • Responsible AI practices
  • Data visualization
  • Clean energy procurement
  • Risk frameworks

What the JD emphasized

  • 6 years of experience in energy strategy, infrastructure development, or portfolio planning within the energy industry, large-scale data center development, or a related capital-intensive sector
  • Demonstrated ability to build integrated financial and market models that connect deal-level economics to portfolio-level outcomes
  • Experience analyzing energy market data, utility rate structures, grid interconnection processes, or power procurement frameworks in the context of large infrastructure portfolios
  • Hands-on experience with wholesale energy markets, including familiarity with pricing structures (LMPs, capacity markets, RECs, PPAs), basis risk, and forward curves
  • Experience building and maintaining complex financial or operational models to support strategic planning and investment decision-making
  • Experience working cross-functionally with Finance, Site Development, and Infrastructure teams to translate analytical outputs into actionable strategic recommendations
  • Experience in communicating complex energy or infrastructure concepts clearly in written and presentation formats to technical and non-technical audiences
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Experience with data visualization tools to build portfolio tracking and reporting solutions
  • Experience supporting data center, hyperscale infrastructure, or large industrial energy strategy in a portfolio planning or development context
  • Experience with energy portfolio optimization or resource planning at scale (10+ gigawatts)
  • Familiarity with clean and renewable energy procurement structures, including power purchase agreements and renewable energy certificates, as they relate to large-scale infrastructure portfolios
  • Experience in building and presenting risk frameworks that quantify exposure across multiple dimensions (market, credit, volumetric, operational)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Proficiency in SQL, Python, or similar tools for large-scale data analysis and automation of analytical workflows