Meta is seeking an experienced, organized, and collaborative Site Selection Manager - Leasing to join the Data Center Site Selection team. We are seeking a Data Center Site Selection Manager who has extensive experience negotiating large, complex leasing deals and an extensive knowledge of the legal agreements that accompany them. The Data Center Site Selection Manager should also have experience thinking both strategically and analytically, develop out-of-the box solutions and can navigate the challenges that accompany leasing projects and portfolios of large magnitude.

Responsibilities

Lead data center acquisition and lease contracting negotiations
• Perform technical due diligence and validate site viability across energy, land, etc
• Manage supplier relationships and best practices
• Perform market analysis and develop leasing site selection strategy
• Stay informed of the technical, market, and regulatory developments in the data center industry
• Contribute to organizational strategy and development of leasing standards at Meta
• Travel domestically (10-25% at times)

Minimum Qualifications
• Bachelor's degree in a business, engineering, environmental, or energy related discipline
• 8+ years experience in facilitating, evaluating, or managing data center capacity projects
• Experience collaborating across multiple internal functions, including legal, compliance, finance, and accounting
• Familiarity with various lease structures (Modified Gross, NNN, YoC, etc.)
• Experience leading large scale data center lease negotiations
• Experience synthesizing commercial, regulatory, market, and contractual details to all organizational levels
• Proven track record building and running leasing programs
• Bachelor's degree in a directly related field, or equivalent practical experience

Preferred Qualifications
• 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