Senior Data Architect, Legal Operations

Summary

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.

Preferred Qualifications

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

Minimum Qualifications

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