Job 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. 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

Requirements

Must-haves

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

Nice-to-haves

Bachelor's degree in Computer Science, Data Science, Information Systems, or related field (or equivalent experience); Master's degree preferred

Application prep

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Keywords to mirror

aisqlpythonml

Platform: apple
Effort: medium

Benefits

Benefits detected in the listing.

Vision