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Meta

Data Center Capacity & Network Manager

Career Insights for Data Manager

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Based on New Mexico data

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What they do

A Data Manager manages databases and coordinates data collection and analysis for a company or organization. Develops procedures for documentation and data storage. Performs or manages data analysis for studies, projects and reports.

$141,442 / year median in New Mexico

+9% projected growth

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Job Description

Meta is hiring a Data Center Capacity and Support Manager to lead the deployment of hyperscale data centers. This central role leads a team of network engineers and coordinates with partners, vendors, and managed service providers to ensure that projects are completed in a timely manner. The manager will build and scale the team, focusing on ownership, speed, quality, and efficiency. Responsibilities include hands-on technical contributions, including design, deployment, and troubleshooting, demonstrating domain expertise and technical impact.
Qualifications:
8+ years of experience in network engineering in large-scale data center network deployments, including hands-on responsibility for planning, building, or migrating production networks Experience with network incident management, change control processes, and operational tooling for monitoring and alerting in enterprise environments Experience collaborating with cross-functional partners including facilities, real estate, and infrastructure teams to deliver network services on time and at scale 5+ years of experience managing / leading network engineering teams involved with large-scale network and wireless deployment programs across multiple physical sites, including hiring, performance management, and team development Experience in large-scale network platforms designed for massive scale, high-bandwidth, and ultra-low latency Knowledge of various scripting languages and/or programming language principles Familiar with packet-based switching, optimized for AI traffic Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 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)