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Program Development Manager, Data Center Design and Construction

Job in Menlo Park, San Mateo County, California, 94029, USA
Listing for: Meta Careers
Full Time position
Listed on 2026-10-11
Job specializations:
  • Management
    Project & Program Management, Operations Management
Salary/Wage Range or Industry Benchmark: 178000 - 245000 USD Yearly USD 178000.00 245000.00 YEAR
Job Description & How to Apply Below
Join Meta's Data Center Planning & Development team at the forefront of one of the largest infrastructure buildouts in history. As a Program Development Manager, you'll play a pivotal role in shaping the future of Meta's global data center portfolio — driving the planning/preconstruction strategy for both New Build and Lease programs that power AI and billions of connected users.

This is a high-visibility role where your work directly influences multi-billion-dollar investment decisions, GW-scale capacity delivery, and the speed at which Meta can bring new infrastructure online.

- Impact at scale — Decisions to shape a global portfolio measured in gigawatts and billions of dollars.

- Speed & complexity — Meta's infrastructure growth is unprecedented;

- Seat at the table — Direct exposure to VP/Director-level leadership and cross-company strategy.

Program Development Manager, Data Center Design and Construction Responsibilities:

Lead Planning Strategy — Own the end-to-end planning for New Build and/or Lease projects, including cost estimating, site evaluations and procurement/supply chain. Drive strategy to meet capacity demand

Drive Cost & Schedule Excellence — Develop and maintain programmatic-level budgets and scheduling coordination identify risks early and present mitigation strategies to leadership

Capital Expenditure management:
Continuous improvement on baseline costs and cash flow projection for all the planning projects. Coordination with the finance team for budget alignment

Coordinate Cross-Functionally — Serve as the connective tissue between Site Acquisition, Energy, Finance, Capacity planning, Design and Construction (DEC) teams to build an integrated plan of record for each project

Leasing:
Technical analysis of the schedule, cost, and risk assessment for the leasing portfolio

Shape the Portfolio — Perform strategic analysis of the pipeline to optimize site sequencing, resource allocation, and delivery timelines against GW demand targets

Influence Decisions at Scale — Present recommendations and trade-off analyses to meet the capacity plan Study multiple scenarios and drive alignment across pillars on scope, schedule, and budget

Innovate & Improve — Continuously develop new processes, tools, and frameworks that accelerate delivery and reduce cost across the program

Minimum Qualifications:

10+ years of experience in commercial construction management — preconstruction, estimating, scheduling, contracting, and cost management

Demonstrated ability to manage large-scale, complex programs (data centers, mission-critical facilities, or equivalent infrastructure preferred)
Strong financial acumen — comfortable building and defending budgets at the hundreds-of-millions-dollar scale

Expert-level scheduling capability (P6, MS Project, or equivalent) with experience in critical-path analysis and schedule risk assessment

Proven ability to lead without authority across matrixed, cross-functional organizations

Exceptional communication and presentation skills — ability to distill complex technical information into clear, actionable narratives for executive audiences

Track record of identifying process improvements and driving them to implementation

Preferred Qualifications:

Familiarity with power/energy procurement timelines and how they intersect with construction delivery

Knowledge of site selection criteria and due diligence processes

Experience managing supply chain and procurement at a programmatic (multi-project) level

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…
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