Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Jun 23, 2026. Meta scores B on the Alion truth index.
Meta’s data centers form the backbone of our global infrastructure, powering the platforms and services that connect billions of people every day.
Responsibilities
Lead a strategic, mission-critical function within Data Center Engineering and Construction (DEC), directly accelerating capacity delivery across a multi-billion-dollar portfolio Own and govern integrated master schedules, schedule baselines, critical path analysis and schedule metrics across multiple concurrent data center development projects, ensuring alignment across portfolio and project lifecycles Lead technical integration efforts by coordinating across civil, structural, mechanical, electrical, and connectivity/network disciplines to identify and resolve cross-system dependencies, creating a single, unified workflow for identifying risks proactively, accelerating capacity decisions and achieving maximum operational efficiency Lead a team of schedulers and technical integration professionals, including full-time employees and contingent workers, providing direction, development, and performance oversight Establish and maintain schedule baselines, critical path analyses, and earned value metrics to provide accurate forecasting and early identification of schedule risks Partner directly with Design, Engineering, and Construction delivery teams to develop and maintain the most efficient and technically correct schedule logic, ensuring that approved acceleration levers are fully realized on the ground and develop recovery plans and mitigation strategies when schedule deviations are identified Serve as the single accountable leader for ensuring "schedule is the source of truth," translating complex technical scope and probabilistic risks (P50, P90) into actionable executive-grade narratives for senior leadership and partners to accelerate strategic decision-making Drive standardization and continuous improvement of schedule development methodologies, project review and risk identification processes, and reporting cadences across the data center project portfolio Collaborate with the Project Controls function to ensure that cost and schedule data are integrated and support accurate capital expenditure forecasting Drive the strategic shift from manual schedule administration to an AI-native technical oversight model, prioritizing speed to market as the central objective for all future infrastructure builds
Qualifications
Experience in developing and managing integrated master schedules using industry-standard scheduling tools such as Primavera P6 or Microsoft Project Experience leading cross-functional teams across engineering, procurement, and construction disciplines on complex, multi-phase development programs 10+ years of experience in project controls, schedule management, or technical integration on large-scale capital construction or infrastructure programs Experience in communicating schedule performance, technical risks, and mitigation strategies to senior leadership and executive stakeholders Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Familiarity with Owner-Furnished Equipment procurement processes and their integration into construction schedules Experience with project management platforms such as Procore, Oracle Primavera Cloud, or Unifier in a capital program context Experience in data center development, mission-critical facility construction, or large-scale energy infrastructure programs 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 schedule workflows, automate reporting, or drive measurable improvements in forecast accuracy

