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
Minimum Qualifications
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
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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
Preferred Qualifications
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 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
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