Data Platform & Governance Manager

Meta; Austin, Menlo Park, San Francisco, New York (TX, CA, CA, NY); On-site; USD 170,000 - 240,000; Full time

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.

Skills

Executive stakeholder collaboration

Milestones & progress communication

AI/ML product delivery

Generative AI tools usage

Data engineering foundations

Roadmap development

Mentoring and developing talent

Ambiguity management

Education

Bachelor's degree in CS/Engineering or related field

Graduate degree in CS/Data Science/Statistics/Engineering

Tools

SQL

Python

Airflow

Data orchestration tools

Job description

About the Team

Data Foundations & Infrastructure (Data Foundations & Infrastructure) is a newly established team within Workforce Strategy & Insights (Workforce Strategy & Insights), responsible for owning and delivering data foundations and scalable support for reporting, analytics, and AI-readiness across WSI and for People@ at scale. We partner closely with Workforce Planning and Headcount Management teams, People Analytics (workforce insights and engagement), and enterprise stakeholders to ensure that workforce data powers executive decision-making across Meta.

This role will lead two critical pods within DFI:

AI Enablement: Develop, evaluate, and productionalize AI agents that scale analyst impact and deliver trusted, intelligent insights across workforce management domains.

Data Infrastructure and Automation Tools: Build, maintain, and modernize scalable data pipelines, automation tooling, and access management to revamp operations for efficiency and AI readiness.

The Role

We are looking for a Senior Analytics Manager to lead the data foundations and AI capabilities that workforce intelligence at Meta runs on — owning both the pipelines and automation tooling that produce our data and the AI agents that consume it. This is a leadership role at the intersection of data engineering, AI productionalization, and workforce analytics — reporting directly to the Director of DFI.

You will manage two established pods, each with an experienced pod lead, and own the strategy that connects them: building pipelines and automation optimized for agent consumption, and building the agents that turn them into trusted insights. You'll set technical direction and operating model, modernize legacy pipelines and consolidate self-service tooling, and partner deeply across People, Infrastructure & Engineering (PIE), Data Governance, Workforce Management, People Analytics, and Finance.

This is a net-new role with significant latitude to shape the operating model and technical direction of both pods — with direct visibility to VP+ leadership and company-wide impact on how Meta plans and manages its 70,000+ person workforce.

• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
• Experience influencing and partnering with executive stakeholders (VP+) across technical and business functions
• Experience defining measurable milestones and communicating delivery progress and business impact to non-technical stakeholders
• 12+ years of progressive experience in data analytics, data engineering, or a related quantitative field
• 6+ years of people management experience, including managing senior ICs or team leads across data engineering and/or analytics teams
• Demonstrated experience leading AI-native transformations — shipping AI/ML-powered products, LLM-based agents, or automated analytics solutions from concept to production
• Hands-on experience with generative AI tools and large language models (LLMs) for analytics, reporting, and automation
• Experience building evaluation frameworks and quality standards for AI/ML outputs
• Strong technical foundation in SQL, Python, and data pipeline orchestration (Airflow, Dataswarm, or equivalent)
• Track record of defining and executing multi-quarter technical roadmaps for data infrastructure modernization at scale
• Experience building or modernizing pipelines and self-service automation tooling used by analysts and downstream products
• Experience managing data governance, access controls, and compliance for sensitive data domains
• Familiarity with HRIS systems (Workday), enterprise data architecture, and HR data structures
• Background building or managing AI agent systems, including skills development, evaluation pipelines, and productionalization workflows
• Experience designing metric semantics, context libraries, or semantic layers that both human-facing products and AI agents consume
• Experience operating amid ambiguity and in-flight roadmaps, converting it into decision frameworks
• Demonstrated track record of mentoring and developing technical talent across career stages
• Experience preparing data platforms for agentic consumption — metadata quality, lineage, and certification at scale
• Experience at a large-scale technology company managing analytics or data engineering teams supporting corporate functions
• Experience in People/HR analytics, workforce planning, or enterprise data domains
• Graduate degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field