基础设施数据治理容量工程师

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

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

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 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 managing ambiguity, and a track record of learning new tools, domains, or methods to address evolving challenges

Experience influencing partner teams across infrastructure, engineering, planning, supply chain, data center, networking, operations, analytics, and finance organizations

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

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

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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.