Product Data Operations Program Manager

Meta•Redmond, WA

1d•$140,000 - $198,000

About The Position

Meta is seeking a Product Data Operations Program Manager to drive the strategy, execution, and continuous improvement of data operations programs that power product development across Meta's portfolio. In this role, you will lead complex, cross-functional initiatives that bridge product, engineering, data science, and operations teams — ensuring that data pipelines, labeling workflows, and data quality programs are designed and delivered at scale. You will define operational frameworks, identify systemic inefficiencies, and translate ambiguous product data needs into structured, repeatable processes that accelerate product decision-making and model development.

Requirements

6+ years of experience in program management, technical operations, or data operations within a technology or product development environment
Experience managing cross-functional programs that involve data pipelines, data labeling, annotation workflows, or data quality processes at scale
Experience defining operational frameworks, process documentation, and program governance structures for ambiguous or rapidly evolving problem spaces
Experience using data and metrics to diagnose operational inefficiencies, measure program health, and drive evidence-based decisions
Experience communicating program status, risks, and recommendations in writing to both technical and non-technical stakeholders

Nice To Haves

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience coordinating with external vendors or outsourced operations partners on data production programs
Demonstrated ability to build scalable operational playbooks and drive adoption across distributed, cross-functional teams
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Familiarity with data quality methodologies such as inter-annotator agreement, sampling strategies, or defect rate analysis
Experience working with machine learning data operations, including training data collection, ground truth labeling, or model evaluation pipelines

Responsibilities

Define and drive end-to-end program strategies for product data operations initiatives, including data collection, annotation, quality assurance, and pipeline readiness
Partner with product, engineering, and data science teams to translate data requirements into scalable operational workflows and delivery plans
Establish program governance frameworks including milestone tracking, risk identification, escalation paths, and cross-functional accountability structures
Identify systemic bottlenecks in data operations workflows and lead process improvement efforts that increase throughput, quality, and cost efficiency
Develop and maintain program health metrics and reporting mechanisms that provide visibility into data pipeline status, labeling accuracy, and operational performance
Lead vendor and operations partner coordination for data labeling and annotation programs, ensuring quality standards and delivery timelines are met
Drive alignment across product and operations leadership on data readiness requirements, capacity planning, and prioritization trade-offs
Synthesize complex operational data into clear written communications and structured recommendations for product and engineering stakeholders
Contribute to the development of team-wide best practices, tooling standards, and playbooks for scaling data operations programs across product areas