Product Data Operations Program Manager

Meta Platforms Inc

  • Burlingame, CA
  • 6 days ago

    Highlights

    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. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.

    Numbers & Facts

    LocationBurlingame, CA

    Description

    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.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 areas6+ 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 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 pipelinesMeta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here .Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form .

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