Data Center Central Planning Lead

Job description

We are looking for a Data Center Central Planning Lead to join Meta's Data Center Strategic Planning organization. In this role, you will own and lead the development of end-to-end, constraint-aware data center capacity plans that translate product growth, AI workload evolution, and fleet architecture into executable roadmaps across power (MW), cooling, space, and network. You will operate at the intersection of capacity engineering, portfolio planning, and investment decisioning, building quantitative models and scenario plans that inform multi‑billion‑dollar infrastructure choices.

You will be expected to go deep in the data and engineering constraints while also serving as a trusted advisor to senior leaders, shaping direction through clear recommendations, executive-ready narratives, and cross‑org alignment.

This is an individual contributor leadership role

success is defined by technical rigor, durable planning mechanisms, and sustained influence across organizations—including the ability to advise, challenge, and align senior stakeholders.

Responsibilities

• Own long-range capacity planning and strategy (LRP) to connect demand signals (product + AI) to data center supply plans and execution paths across MW delivery, space readiness, and network capacity—including multi‑year roadmaps, supply and demand matching, and key decision points
• Build and maintain quantitative planning models (supply/demand, portfolio allocation, sensitivity analysis, bottleneck identification, schedule-risk and uncertainty modeling), and use them to drive investment prioritization and sequencing
• Translate workload characteristics (GPU/AI clusters, rack power density, resiliency tiers, topology/interconnect needs, placement constraints) into facility and electrical requirements including MW ramp profiles, readiness gates, and deployment constraints
• Lead assessment of system-level constraints across fleet and pipeline (utility delivery timelines, substation/transformer capacity, cooling technology limits, heat rejection, building envelopes, network ingress/egress, construction sequencing) and drive mitigation strategies with clear owners, timelines, and success criteria
• Develop executive decision packages: synthesize complex analyses into crisp trade-offs and recommendations (cost, schedule, reliability, operability, risk), explicitly calling out assumptions, sensitivities, and "what changes the answer." Advise and influence senior Meta leadership by framing options, aligning stakeholders pre‑readout, and driving decisions in forums with competing priorities—while maintaining technical credibility with engineering partners
• Drive cross-functional execution and accountability: align roadmaps, surface gaps early, manage escalations, and ensure closure through programmatic follow-through and planning governance
• Establish and continuously raise the planning "bar": define assumption governance, model review cadence, metric definitions, documentation standards, and reproducibility so plans are auditable, repeatable, and resilient to ambiguity

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 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