Senior Data Architect, Legal Operations

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. 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 data quality and adoption of standards Lead and mentor the DMO team, including Senior Data Engineer and Data Analysts Set technical direction and standards for the team; review designs and implementations 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 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

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