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Meta's Business Messaging and Business AI team is at the forefront of how businesses connect with customers through messaging platforms used by billions of people worldwide. We're building the future of business communication — helping millions of businesses of all sizes reach, engage, and support their customers through personalized, real-time conversations at scale. The Marketing Technology & Operations (MarTech & Ops) function within Business Messaging & Business AI Marketing is the connective tissue between data, campaign execution, and analytics. We enable marketing teams to move faster and smarter — powering the systems, processes, and insights that turn go-to-market strategy into measurable business impact. If you thrive at the intersection of marketing, data, and technology, this is where you'll have the most leverage. As the MarTech Strategic Operations Lead for Business Messaging Marketing and Business AI, you will be the architect and orchestrator for operational precision across data, campaign operations, and analytics/reporting. You will unify these functions to enable scalable, data-driven marketing and measurable business impact. This is a strategic individual contributor role that requires cross-functional leadership, direction, and the capacity to connect business, technical, and operational teams.
Job Responsibility:
Develop and maintain the operational strategy and roadmap for MarTech, integrating data, campaign execution, and analytics/reporting to support enterprise go-to-market goals
Build and optimize processes for campaign intake, execution, QA, and reporting, with a focus on automation, scalability, and compliance
Define and track operational KPIs, and communicate progress to leadership and stakeholders
Demonstrate self-sufficiency in understanding and navigating data infrastructure, enabling you to independently validate data, troubleshoot issues, and partner effectively with technical teams
Translate business needs into technical requirements, ensuring data pipelines, campaign automation, and reporting systems are robust, privacy-compliant, and scalable
Guide and influence technical teams (Data Engineering, Analytics, Platform Engineering) to deliver on strategic priorities
Champion the development and adoption of unified reporting and analytics tools, enabling self-serve insights and data-driven decision-making for business stakeholders
Lead the operationalization and execution of marketing campaigns, ensuring reliability, scalability, and speed
Standardize campaign intake, build, QA, and reporting processes
Identify and drive automation opportunities to reduce manual effort and accelerate campaign delivery
Act as the primary liaison between Marketing, Sales, Product, Partnerships, and Data/Analytics teams, driving alignment on priorities, dependencies, and timelines
Lead cross-functional working groups, ensuring clarity, accountability, and joint ownership of outcomes
Proactively identify and resolve operational bottlenecks, data gaps, and process inefficiencies
Standardize documentation, best practices, and enablement materials for MarTech tools and workflows
Communicate program status, risks, and wins to leadership and stakeholders with clarity and confidence
Foster an environment of transparency, collaboration, and continuous improvement
Requirements:
10+ years in strategic operations, technical program management, or MarTech/data operations in a complex, cross-functional environment
Experience turning large, abstract business problems into structured workstreams and scalable solutions
Proven experience integrating data, campaign operations, and analytics/reporting at scale
Self-sufficiency in technical environments: query, validate, and interpret data (e.g., SQL, analytics tools), while focused on enabling and guiding technical teams rather than hands-on execution
Analytical experience with marketing measurement, attribution, and reporting
Cross-functional leadership, stakeholder management, and communication skills
Nice to have:
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies