Capacity Engineer, Infrastructure Data Governance

Meta is seeking a Data Governance Engineer to build and scale data governance across infrastructure planning and supply chain organizations and systems. This role will define and operate how critical infrastructure data is governed end to end, from intake and ownership through quality, controls, and adoption, so teams can make high-quality decisions, operate efficiently, and execute reliably at Meta scale.

We will do this primarily by building software, mathematical models, and automated tracking of key performance metrics that make data quality, lineage, and control health measurable rather than aspirational. You will translate ambiguous governance needs into clear technical requirements, operating models, roadmaps, milestones, and measurable outcomes.

This role is very cross-functional and provides an opportunity to work with supply chain partners, infrastructure engineering, planning, data center, networking, data science, analytics, finance, and operations teams to power the rapid growth of Meta's products. This is a senior individual-contributor role. The right candidate brings demonstrated technical judgment in evaluating tradeoffs across data systems, governance models, or infrastructure decisions, structured program leadership, clear written and verbal communication, including the ability to convey technical concepts, program status, and recommendations to diverse stakeholders, and the ability to influence partner teams and stakeholders across multiple infrastructure organizations without relying on authority.

Responsibilities

Own the end-to-end governance process for a major domain of critical infrastructure data including intake, ownership, definitions, quality expectations, review cadences, decision rights, escalation paths, change management, and compliance monitoring
Develop and analyze business, manufacturing, and logistics data to identify governance gaps, source-of-truth conflicts, and data defects that degrade supply chain and capacity decisions
Establish durable operating mechanisms that clarify data ownership, stewardship responsibilities, source-of-truth expectations, approval flows, audit trails, exception handling, and accountability across teams
Drive cross-team adoption of governance standards and work with partner teams to ensure compliance with agreed internal processes, quality bars, and operating rhythms
Contribute to end to end supply chain processes, methodologies, and data to deliver an executable and optimized supply plan grounded in trustworthy inputs
Manage and resolve critical escalations and data exceptions across the supply chain
Identify technical dependencies, risks, sequencing constraints, rollout criteria, adoption blockers, and measurable success indicators across multiple teams
Work cross-functionally to define problem statements, collect data, build analytical models, and make recommendations that drive change
Communicate program strategy, status, risks, decisions, compliance health, and impact clearly to technical teams, cross-functional partners, and stakeholders
Create and maintain high-quality artifacts, including governance charters, technical program plans, roadmaps, ownership and RACI models, dependency trackers, risk and mitigation plans, rollout plans, compliance dashboards, and leadership updates
Improve how Meta executes infrastructure data governance by simplifying processes, scaling repeatable patterns, and mentoring peers and cross-functional partners

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
8+ years of experience in operations research, industrial engineering, supply chain management, systems engineering, technical program leadership, or related field
Experience contributing to or leading data governance or data management programs, including governance processes, ownership models, standards, controls, adoption mechanisms, or compliance tracking
Experience delivering technical programs or products from inception to launch across multiple teams 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
Experience defining metrics, control health indicators, adoption measures, compliance dashboards, or review mechanisms for technical governance programs
Experience in infrastructure operations and technical infrastructure knowledge
Experience interfacing with and establishing relationships with management at suppliers or customers
Experience communicating and translating technical and non-technical requirements for cross-functional stakeholders
Experience working with cross-functional teams
Experience managing ambiguity, and a track record of learning new tools, domains, or methods to address evolving challenges
Experience mentoring engineers and raising the quality of program execution
Experience influencing partner teams across infrastructure, engineering, planning, supply chain, data center, networking, operations, analytics, and finance organizations
Experience working with distributed systems at scale
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)
3+ years of experience in coding/scripting languages such as Python, R, Java, C, C++, PHP
Technical understanding of infrastructure data domains, such as demand planning, capacity planning, inventory, sourcing, procurement, logistics, deployment, data center operations, networking, asset lifecycle, or service capacity
Masters or Ph.D. degree in Operations Research, Industrial Engineering, Computer Science, or related technical field
Experience with source-of-truth strategy, master data management practices, data quality frameworks, metric definitions, lineage, stewardship models, or data operating models
Experience transforming business systems and models and achieving results relative to goals, including identifying opportunities to challenge existing approaches and proposing data-driven alternatives
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience with data governance programs in infrastructure, supply chain, data center, networking, capacity planning, logistics, finance, or similarly complex operational domains
Experience driving programs across centralized platforms and federated business or infrastructure teams
10+ years of technical, manufacturing operations, or technical program leadership experience in the hardware systems or infrastructure industry