基础设施数据治理容量工程师

Own the end-to-end governance process for 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 all areas of the supply chain

Identify technical dependencies, risks, sequencing constraints, rollout criteria, adoption blockers, and measurable success indicators across multiple infrastructure organizations

Work cross-functionally to define problem statements, collect data, build analytical models, and make recommendations that drive change across infrastructure organizations

Communicate program strategy, status, risks, decisions, compliance health, and impact clearly to technical teams, cross-functional partners, and executive stakeholders

Create and maintain high-quality artifacts, including governance charters, technical program plans, cross-org roadmaps, ownership and

RACI models, dependency trackers, risk and mitigation plans, rollout plans, compliance dashboards, and executive updates

Improve how Meta executes infrastructure data governance by simplifying processes, scaling repeatable patterns, and mentoring senior ICs and cross-functional partners

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

10+ years of experience in operations research, industrial engineering, supply chain management, systems engineering, technical program leadership, or related field

Experience leading data governance or data management programs, including establishing end-to-end governance processes, ownership models, standards, controls, adoption mechanisms, and compliance tracking

Experience delivering technical programs or products from inception to launch across multiple teams or organizations

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

Proven experience interfacing with and establishing relationships with management at suppliers or customers

Experience leading data governance programs in infrastructure, supply chain, data center, networking, capacity planning, logistics, finance, or similarly complex operational domains

12+ years of technical, manufacturing operations, or technical program leadership experience in the hardware systems or infrastructure industry

Experience influencing senior leaders across infrastructure, engineering, planning, supply chain, data center, networking, operations, analytics, finance, and business organizations

Experience communicating and translating technical and non-technical requirements for cross-functional stakeholders

Experience mentoring senior ICs and raising the quality of program execution across an organization

Experience transforming business systems and models and achieving results relative to goals, including questioning the norm and identifying non-obvious solutions

Experience driving programs across centralized platforms and federated business or infrastructure teams

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

Experience defining metrics, control health indicators, adoption measures, compliance dashboards, or review mechanisms for technical governance programs

Experience defining source-of-truth strategy, master data management practices, data quality frameworks, metric definitions, lineage, stewardship models, or data operating models

Masters or Ph.D. degree in Operations Research, Industrial Engineering, Computer Science, or related technical field

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Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

10+ years of experience in operations research, industrial engineering, supply chain management, systems engineering, technical program leadership, or related field.