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Meta is standing up a dedicated strategic-planning function to manage billions of dollars of data center investment and a global capacity roadmap, signaling that AI-driven infrastructure buildout is now being run as a centralized, executive-level capital allocation problem.
We are looking for a Data Center Strategy & Planning Manager with experience in developing infrastructure strategies and programs to join the Strategic Planning team within the Data Center organization. In this role, you'll be part of the team that builds Meta’s global data center roadmap, develops end to end infrastructure scaling strategies, and develops plans to drive efficiency in our infrastructure that set the direction for one of the fastest growing platforms in the world. As a Data Center Strategy & Planning Manager, you will be accountable for driving investment decisions that cover billions of dollars and help scale our data center footprint efficiently to meet our growing product and service needs. This is a unique opportunity where you will be responsible for developing and leading transformational strategic initiatives and capacity programs from inception, evaluating trade-offs, and driving recommendations to executive leadership, and taking them through implementation. This is an individual contributor role, where you’re at home rolling up the sleeves and being in the details, as well as being experienced to think big picture, project manage complex initiatives, and influence partner teams to change the status quo. This is a highly cross-functional role where you will be expected to partner with our data center capacity stakeholders (capacity engineering, network engineering, construction, site selection, site & facility operations, network, finance).
Leverage technical experience and expertise to identify and build large transformational programs and initiatives across Infrastructure that scale Meta’s Data Center footprint efficiently Develop new Data Center planning strategies that focus on driving improvements in reliability and achieving cost and operational efficiency, including reductions in deployment times, improvements in data center power utilization, and service placement optimizations Optimize network, hardware, and DC infrastructure footprints to drive efficiency Develop detailed project evaluation plans for data center plan evolution and set the pace to drive the closure of the project Apply quantitative techniques, develop decision scenarios and trade-offs to drive multi-billion dollar infrastructure decisions at the highest level of the organization Own the communications strategy for data center planning decisions, which includes executive-level and detailed project briefs and status updates Use technical judgment to drive new project evaluations, technology reviews, and proposals to build consensus
Bachelor's degree in a directly related field, or equivalent practical experience 10+ years of experience working in Infrastructure/Cloud/Hardware with a background in strategy, capacity planning, supply chain optimization, technology strategy consulting Experience distilling various data points into actionable insights and recommendations, to quickly separate signal from noise for executive communication and decision-making Business acumen, with the ability to synthesize incomplete information into structured analyses, with the experience to form and refine hypotheses into an actionable analysis and a recommendation Problem-solving and strategy skills, including expansive opportunity identification and framing of complex/ambiguous problems Experience in completing multiple cloud, infrastructure, and hardware efficiency or optimization projects Technical experience in infrastructure, hardware, or similar designs Experience in collaborating and working with internal and external organizations and individuals 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) Master's degree in a relevant field Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
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