<p>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.</p> <p>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.</p> <p>Experience building data architectures for legal tech or legal operations environments Familiarity with legal systems including matter management, CLM, eBilling, or document management systems Experience with semantic layer technologies (dbt Semantic Layer, Cube, AtScale), knowledge graphs (Neo4j), or ontology design Understanding of how data architecture enables AI/ML systems, including RAG, embeddings, vector databases, and context management Experience with data observability and quality tools (Monte Carlo, Great Expectations, or similar) Knowledge of data privacy, compliance, and governance frameworks relevant to legal data</p> <p>Bachelor's degree in Computer Science, Data Science, Information Systems, or related field (or equivalent experience); Master's degree preferred 10+ years of experience in data architecture, data engineering, or related fields, with at least 4 years in a senior architecture or leadership role Deep expertise in enterprise data architecture including data modeling, dimensional modeling, data lake design, and ETL/ELT patterns Strong experience with cloud data platforms, particularly Snowflake Proficiency in SQL and Python for data engineering, transformation, and automation Experience with data integration and transformation tools (dbt, Fivetran, or similar) Experience designing and implementing entity resolution, master data management, or data quality solutions Proven experience leading and mentoring data teams Excellent communication skills - able to translate data architecture concepts for technical and non-technical audiences</p>