Job description

Integrity & Support Enablement (ISE), within Integrity & Support Operations (ISO), is a strategically-minded team building the shared architectures that enable Global Operations (GO) to operate from a single source of truth. The data architecture function within ISE ensures that operational data flows coherently between systems, that cost is attributed consistently, and that teams across GO speak a common language, so every team can measure, decide, and build without reinventing definitions. We are looking for a full-time Data Architecture Program Manager to join us. This is a function-building role: you will establish and scale the data governance and architecture practice for GO, defining the standards, frameworks, and integration patterns that multiple teams build on. Our program managers translate complex operational and technical requirements into shared data models, classification frameworks, and cross-system integration designs. They work closely with data science, engineering, and operations partners, serving as the connective layer between technical and non-technical stakeholders, and they deliver canonical structures that power decision-making at scale. Define and govern shared operational data models and classification frameworks used across multiple teams and systems; establish architectural standards designed to scale beyond any single team or program Translate business requirements into data architecture designs, mapping how information should be structured, stored, and integrated to drive informed decision-making and measurable outcomes Develop a deep understanding of how data flows between operational systems to identify gaps, inconsistencies, and opportunities for standardization Drive cross-functional alignment on shared definitions, integration standards, and field-level agreements between teams where no single team has unilateral authority Manage schema evolution and breaking changes across dependent systems, including deprecation planning, coordinating dependent teams through transitions, and stakeholder communication Partner with data science and engineering teams to translate architectural decisions into production-grade data products and pipelines Design cost attribution and resource modeling that ensures budget and workforce data reconciles end-to-end Anticipate future data needs across operational teams and proactively design canonical structures before teams build in isolation Set the long-term data architecture strategy for GO, shaping roadmaps across product, engineering, and operations partners Enable the development of internal tools and decision systems by defining the data requirements, specifications, and governance frameworks they depend on Develop data architecture capability across the broader organization by mentoring program managers and embedding architectural thinking in teams across GO Bachelor's degree in a directly related field, or equivalent practical experience BA/BSc degree in a quantitative, technical, or related field, or equivalent practical experience 7+ years of program management or technical program management experience in a data-intensive technical environment Demonstrated experience designing data models, taxonomies, or classification systems adopted across multiple teams or organizations Ability to reason about data structures, schemas, pipeline architecture, and system integrations, including translating these concepts across technical and non-technical audiences Proven track record of driving cross-functional consensus on shared standards or definitions, including with director- or VP-level stakeholders Experience translating complex technical decisions for executive audiences and driving adoption across organizational boundaries Experience leading schema governance or data standards programs end-to-end, including deprecation planning and migration coordination Analytical thinking and structured problem-solving at scale Experience working across global, multicultural teams 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 Experience building internal tools or decision systems from requirements through adoption (not just consuming them) Experience working in a technology company or fast-paced global operations environment Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience with data pipeline orchestration, warehouse architecture, or ETL design Experience with operational data in customer support, content moderation, trust & safety, or workforce management domains Background in cost attribution, budget modeling, or operational finance Experience managing schema governance and breaking changes across a large, distributed engineering organization Proficiency in SQL and relational databases Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Track record of establishing data governance frameworks or canonical standards adopted at org or company scale Prior experience building or scaling a data architecture function from early stage

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