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Director, Data Engineering

United States, Menlo Park 253000.00 - 314000.00 USD / Year · Job Posted May 13, 2026
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Job Description

You'll be one of the analytics leaders for how Meta transforms its Enterprise through AI. This is a 0→1 role with enterprise-wide scope, high ambiguity, and direct visibility to leadership. If you want to shape how 70,000+ people work—and measure whether it's actually working—this is the job. We are open to hiring Data Science or Data Engineering profiles. In our world, both are Analytics. The work will span the full spectrum—from building the data infrastructure that powers enterprise measurements to shaping the strategic frameworks that define what "good" looks like. Your title matters less than your demonstrated experience to operate across that range.

Job Responsibility

  • Firefighter Mode: Leadership asks "what's the ROI of [new AI tool]?" on Wednesday. You have an answer by Friday
  • A team claims their AI initiative saved 10,000 hours. You validate (or invalidate) it
  • You rapidly instrument, measure, and communicate whether it's working
  • You jump into whatever is urgent and ambiguous—and you close it
  • Systems Thinker Mode: Build measurement frameworks that work across wildly different AI tools and use cases (coding, analytics, recruiting, HR support, supply chain, finance and more)
  • Create the dashboards, workspaces, semantic models and self-serve layers that let stakeholders across the company understand progress without pinging you
  • Design and scale the data pipelines and instrumentation that capture agent telemetry, usage signals, and outcome metrics across a fragmented and fast-moving tool landscape
  • Shape the strategy for how we think about productivity, time savings, and quality improvements in an AI-augmented workforce
  • Influence how Analytics (and business functions) evolve their operating models, job profiles, and organization structures for the AI era

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • AI power user. You're already a power AI user in your day-to-day work—Metamate, Claude, Cursor, or whatever tools make you faster. You'll set an example for what "AI-native" looks like and help others get there
  • 0→1 builder experience You've built measurement systems from scratch in ambiguous spaces. You don't wait for requirements—you define them
  • Speed + rigor. You can move fast without being sloppy. You know when to be 60% right now vs. 95% right later
  • Executive communication. You'll regularly present to leadership. Your insights need to be crisp, actionable, and defensible
  • Cross-functional influence. You'll work across dozens of teams (EE, Security, CPP, DevInfra, and more). You need to drive alignment without authority
  • Honesty. Some AI initiatives won't work. Some claimed impact will be inflated. You'll need to call it like you perceive it

Nice to have

  • 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 with productivity/efficiency measurement, internal tools, or enterprise products
  • Familiarity with LLMs, agentic systems, or AI tooling
  • Prior experience in a founding/early team member role

What we offer

  • bonus
  • equity
  • benefits

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