We are seeking a Data Architect to join our Claims Technology organization, leading the design and governance of a canonical claims ontology that enables semantic interoperability and AI-driven decisioning across our global digital claims platform. This role is foundational to scaling automation, improving data consistency, and enabling intelligent decision-making across systems and regions, acting as the critical bridge between claims operations, enterprise Information Architecture, and engineering pipelines. Responsibilities Design and evolve a canonical claims ontology, including entities, relationships, hierarchies, and business semantics, ensuring alignment with industry standards and enterprise needs Translate complex artifacts, such as existing payloads, schemas, and legacy middleware, into a formal, structured data model Define how the ontology is deduced practically Partner with engineers to define and build proper GenAI extraction pipelines capable of parsing complex legacy artifacts Support AI-driven decisioning by enabling structured context for LLMs, improving recommendation accuracy and automation outcomes Enable consistent data interpretation across systems by defining semantic alignment Ensure the pragmatic semantic layer built for the FNOL flow syncs with and informs the broader enterprise ontology efforts and Information Architecture standards Establish and govern controlled vocabularies, semantic consistency, and regional variations across business domains Help establish and define the operating model for the ontology's maintenance and lifecycle, including strict governance processes around making changes, managing business approvals, handling versioning, and dictating what concepts belong inside or outside the semantic boundary Collaborate with domain experts, architects, and engineering teams to translate business concepts into structured semantic models and drive adoption Requirements 10+ years of experience in data architecture or related roles Understanding of insurance claims or financial services domains, including data structures, workflows, and regulatory considerations Background in ontology modeling, knowledge graphs, or metadata frameworks, with the ability to translate business meaning into structured models Capability to make sense of complex technical artifacts, such as JSON payloads, API contracts, and legacy middleware mappings, and extract the underlying business semantics Proficiency in conceptual and logical data modeling, data architecture, and enterprise data governance practices Fluency in English, with a minimum B2+/C1 level for effective communication Nice to have Knowledge of how LLMs can be utilized for metadata extraction, semantic mapping, context modeling, and document parsing Familiarity with ACORD style structures or other canonical payloads used in major insurance claims platforms