Senior Data Architect, Legal Operations

Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Are you passionate about building data foundations that power intelligent systems and strategic decision-making? Do you thrive at the intersection of data architecture, governance, and enterprise transformation? Can you translate complex data challenges into elegant, scalable solutions? The Applied Data Science team within Legal Operations is building the data foundation that powers AI and analytics for a global legal organization. We're transforming how legal work gets done - and it starts with trusted, connected data. The Principal Data Architect leads the Data Management Office (DMO) and owns the data architecture vision that makes AI accurate and analytics reliable. Description The Senior Data Architect owns the data architecture vision for Legal Operations and leads the Data Management Office. You will design and implement the semantic layer, unified data model, and data governance frameworks that make data trusted, connected, and ready for AI and analytics consumption. This role combines strategic architecture leadership with hands-on technical work and team leadership. Responsibilities: Define and own the enterprise data architecture for Legal Operations, including the unified data model, semantic layer, and integration patterns Design and implement entity resolution to create master records for key entities (law firms, vendors, timekeepers, counterparties) across all legal systems Establish common language, taxonomy, and legal ontology that standardizes terminology across practice groups and systems Architect the data lake and integration layer that connects matter management, contracts, eBilling, document management, and other legal systems Build the data foundation that enables AI systems to achieve production-level accuracy and analytics to deliver trusted insights - providing the context, entity relationships, and data quality required Establish data quality standards, validation rules, and monitoring to ensure data accuracy and completeness Design and implement data governance frameworks including data ownership, access controls, lineage, and compliance Partner with Data Stewards embedded in practice groups to drive d…