Construction Manager - Data Center Design, Engineering, & Construction

Meta Meta · Big Tech · Beaver Dam, WI

This role is for a Construction Manager in Meta's Data Center Design, Engineering, & Construction team. The primary focus is on managing the construction, commissioning, and turnover of data centers, including budget, schedule, and risk management. While the role requires knowledge of AI tools for workflow optimization and ethical AI practices, the core responsibilities are in traditional construction management, not AI development.

What you'd actually do

  1. Manage the construction, commissioning, and turnover of a Data Center within a campus program
  2. Manage the budget associated with the project
  3. Manage the cost change process and negotiate best pricing
  4. Manage the schedule and associated risks to ensure reliable and predictable turnover dates
  5. Manage warranty and tenant improvement work in the live environment when/as necessary

Skills

Required

  • Bachelors in engineering or construction management or equivalent work experience
  • 7+ years of work experience in construction management
  • Multi-Project experience in large scale construction management, mission critical, infrastructure, and or data center construction
  • General knowledge of civil, structural, electrical, and mechanical systems
  • Knowledge of capital budget management and contract administration
  • Negotiation skills and experience providing solutions to problems

Nice to have

  • LEAN Construction knowledge and application of those tools
  • P6 Procore and eBuilder software experience
  • BIM 360 and Bluebeam software experience
  • MS Visio and SharePoint experience
  • Building Environment Accreditations (i.e. LEED, SITES, TRUE, WELL)
  • Proficient working knowledge of MS Word, Excel, and PowerPoint

What the JD emphasized

  • 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