Data Center Strategy & Planning Manager

Meta is seeking a Data Center Strategy & Planning Manager to join the Strategic Planning team within the Data Center organization. In this role, you will be responsible for shaping Meta's global data center roadmap and developing end-to-end infrastructure scaling strategies that support one of the world's largest and fastest-growing compute platforms. You will drive transformational capacity planning initiatives spanning network, hardware, and facility infrastructure, translating complex technical and operational trade-offs into multi-billion dollar investment decisions presented to executive leadership. This is a highly cross-functional individual contributor role requiring deep partnership with capacity engineering, network engineering, construction, site selection, site and facility operations, and finance stakeholders.

Responsibilities

Identify, develop, and lead large-scale transformational capacity planning initiatives that scale Meta's global data center footprint efficiently and reliably Build and evolve data center capacity planning strategies that drive improvements in power utilization, deployment timelines, service placement optimization, and cost efficiency Apply quantitative modeling and scenario analysis to evaluate infrastructure trade-offs and support multi-billion dollar investment decisions at the executive level Develop detailed project evaluation frameworks for data center plan evolution, setting milestones and driving initiatives through to closure Optimize the interplay between network, hardware, and data center infrastructure footprints to unlock operational and capital efficiency Own the communications strategy for data center planning decisions, including executive-level briefings, detailed project status updates, and investment recommendations Partner cross-functionally with capacity engineering, network engineering, construction, site selection, facility operations, and finance to align on planning assumptions and execution priorities Use technical judgment to lead new project evaluations, technology reviews, and infrastructure proposals, building consensus across partner organizations Distill large and varied data sets into clear, actionable insights that separate signal from noise for leadership decision-making Define and refine long-term infrastructure scaling hypotheses into structured analyses and strategic recommendations that influence company-wide data center direction

Qualifications

Bachelor's degree in a directly related field, or equivalent practical experience 12+ years of experience in infrastructure, cloud, or hardware domains with a background in strategy, capacity planning, supply chain optimization, or technology strategy Experience developing and executing large-scale infrastructure efficiency or optimization programs across network, hardware, or data center systems Experience applying quantitative techniques and scenario modeling to drive complex infrastructure investment decisions Experience distilling technical and operational data into executive-level communications, recommendations, and decision frameworks Experience collaborating across engineering, finance, construction, and operations organizations to align on infrastructure planning strategies Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience with data center power infrastructure, cooling systems, or facility design as it relates to capacity and efficiency planning Advanced degree in engineering, operations research, business, or a related technical field Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Demonstrated ability to integrate AI tools to optimize analytical workflows and drive measurable improvements in planning accuracy or efficiency Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience developing capacity planning models that incorporate hardware lifecycle, network topology, and service placement constraints