D. degree in Operations Research, Industrial Engineering, Computer Science, or related technical field 3+ years of experience in coding/scripting languages such as Python, R, Java, C, C++, PHP 12+ years of technical, manufacturing operations, or technical program leadership experience in the hardware systems or infrastructure industry Experience leading data governance programs in infrastructure, supply chain, data center, networking, capacity planning, logistics, finance, or similarly complex operational domains 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 source-of-truth strategy, master data management practices, data quality frameworks, metric definitions, lineage, stewardship models, or data operating models Experience working with distributed systems at scale Experience in infrastructure operations and technical infrastructure knowledge Experience defining metrics, control health indicators, adoption measures, compliance dashboards, or review mechanisms for technical governance programs Experience transforming business systems and models and achieving results relative to goals, including questioning the norm and thinking out-of-bounds Proven experience interfacing with and establishing relationships with management at suppliers or customers Experience influencing senior leaders across infrastructure, engineering, planning, supply chain, data center, networking, operations, analytics, finance, and business organizations Experience driving programs across centralized platforms and federated business or infrastructure teams Experience mentoring senior ICs and raising the quality of program execution across an organization 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 technologiesMeta builds technologies that help people connect, find communities, and grow businesses. The right candidate brings deep technical judgment, structured program leadership, crisp written and verbal communication, and the ability to influence senior leaders across multiple infrastructure organizations without relying on authority.