AI-Ready Data Platform & Governance Manager

Austin, Menlo Park, San Francisco, New York (TX, CA, CA, NY)

On-site

USD 170,000 - 240,000

Full time

4 days ago

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Job summary

Meta seeks a Senior Analytics Manager to lead data foundations and AI capabilities powering workforce intelligence. You will own data pipelines, automation tooling, and the AI agents that generate trusted insights.

This leadership role sits at the nexus of data engineering, AI productionalization, and workforce analytics, reporting to the Director of DFI. You will manage two established pods, set strategy, modernize pipelines, and drive a scalable operating model with visibility to VP+

Qualifications

Bachelor's degree or equivalent practical experience.
Experience influencing executive stakeholders (VP+) across technical and business functions.
Experience defining measurable milestones and communicating delivery progress to non-technical stakeholders.
12+ years in data analytics, data engineering, or related field.
6+ years of people management in data/analytics teams.
Led AI-native transformations — AI/LLM-powered products or automated analytics.
Hands-on with generative AI tools and LLMs for analytics, reporting, automation.
Experience building evaluation frameworks and quality standards for AI/ML outputs.
Strong foundation in SQL, Python, and data pipeline orchestration.
Track record of multi-quarter technical roadmaps for data infrastructure modernization.
Experience building pipelines and self-service automation tooling for analysts.
Experience with data governance, access controls, and compliance for sensitive data.
Familiarity with HRIS systems (Workday) and enterprise data architectures.
Experience in building/managing AI agent systems and production workflows.
Experience designing metric semantics and semantic layers for human-facing products and AI agents.
Ability to operate amid ambiguity and translate roadmaps into decisions.
Mentoring and developing technical talent across career stages.
Experience preparing data platforms for agentic consumption — metadata quality, lineage, certification.
Experience in large-scale technology companies supporting enterprise functions.
Experience in People/HR analytics, workforce planning, or enterprise data domains.
Graduate degree in CS/Data Science/Statistics/Engineering.

Responsibilities

Lead two pods: AI Enablement and Data Infrastructure & Automation Tools.
Own strategy connecting both pods: pipelines and automation for agent consumption and AI agents.
Set technical direction, modernize legacy pipelines, and consolidate self-service tooling.
Partner across People, PIE, Data Governance, Workforce Management, People Analytics, and Finance.