Meta Business Services Finance Data & Analytics builds the governed data foundation that Meta's Finance organization runs on - the certified datasets, semantic models, and data products that controllers, accountants, business partners, and AI agents rely on to answer questions and make decisions. We are hiring a Manager, Data Platform & Governance to lead the technical layer of our Finance Data Strategy. This is a hybrid leadership role: you will manage and grow a team of data engineers, set and enforce the platform and governance standards our Finance data domains are built to, and represent the strategy directly with senior Finance and Engineering leaders. You will be accountable for delivery that is visible in real time, and for outcomes that measurably change how Finance teams work day to day.
Responsibilities
Represent the data strategy in forums with senior Finance, business, and engineering leaders - framing technical trade-offs in business terms, driving decisions, and building peer-level credibility across data domains
• Drive prioritization and execution across partner teams outside your direct reporting line, translating business outcomes into a sequenced technical roadmap
• Own a live, cross-domain view of delivery - milestones, owners, dependencies, and status - and connect it to an evidence-backed narrative of business impact for Finance stakeholders
• Provide technical oversight of engineering standards, data assurance, and the business/semantic layer across all Finance data domains, ensuring consistency and quality at scale
• Set and enforce data governance standards: metadata and documentation, metric definitions, glossary coverage, data ownership and pipeline SLAs, schema and naming conventions, and access controls
• Own data quality and observability - monitoring, tiered alerting, lineage and impact analysis, and automated remediation
• Ensure the accuracy and effectiveness of AI agents and analytics tools built on Finance data, including evaluation datasets, accuracy measurement, and sustained quality benchmarks
• Hire, manage, and develop a team of data experts; set role scope, performance expectations, and career growth plans
• Actively mentor team members at various experience levels - pairing on technical work, teaching platform and governance fundamentals, and creating opportunities for them to take on visible ownership
• Partner closely with central Data Engineering and platform organizations, building internal capability while strengthening those relationships
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 12+ years of experience in data engineering, data platform, or data architecture
• 6+ years of experience directly managing technical teams
• Experience owning a data platform or data governance domain end to end at enterprise scale
• Hands-on experience with modern data stacks: distributed warehouses and lakehouse architectures, pipeline orchestration and reliability, semantic/metrics layers, BI and self-service platforms, and data quality tooling
• Experience influencing senior leadership on technical strategy, including presenting to and driving decisions with executive stakeholders
• Experience driving execution across cross-functional teams outside of direct reporting lines
• Experience defining measurable milestones and communicating delivery progress and business impact to non-technical stakeholders
Preferred Qualifications
• Experience building the governed data and evaluation foundations that AI or LLM-based tools depend on, including accuracy measurement
• Experience operating amid ambiguity and in-flight roadmaps, converting it into decision frameworks
• Demonstrated track record mentoring and growing technical talent at various experience levels
• Experience integrating enterprise third-party systems (ERP, HCM/payroll, banking, custodial, or vendor data feeds)
• Experience with Finance, Accounting, Treasury, Tax, Payroll, or FP&A data domains, or a comparable regulated environment with audit and controls requirements
• Experience building a team from a small base, including hiring and developing senior engineers
