Data Architect

Location: Chicago (hybrid)About The CompanyWe are a leading global law firm dedicated to excellence and innovation in serving our clients. Our culture emphasizes collaboration, continuous improvement, and forward-thinking approaches. We leverage advanced technology and data intelligence to drive operational excellence and deliver superior outcomes.Job SummaryWe are seeking a highly experienced Data Architect to join our Data Platform & Engineering organization. Reporting to the Director of Data Platform & Engineering, this role will define and advance the enterprise data architecture that underpins business operations, analytics, and AI strategy.The ideal candidate will possess deep expertise in enterprise data modeling, domain-oriented information architecture, ontology design, and modern cloud data ecosystems. This role will shape how the organization models core business concepts, establishes shared data meaning across domains, and creates a scalable semantic foundation for interoperability, governance, analytics, and reusable enterprise data products.Key ResponsibilitiesEnterprise Data Architecture: Define and govern the enterprise conceptual, logical, and canonical data architecture to support scalable, business-aligned information management and analytics initiatives. Domain Modeling & Semantic Design: Lead the development of enterprise domain models, ontologies, taxonomies, and semantic frameworks that represent core business entities, relationships, processes, and events across major functional areas. Metadata & Governance Strategy: Define and govern metadata architecture, including active metadata strategies, data catalog integrations (Unity Catalog, Alation, Collibra, or equivalent), lineage management, and governance standards across the Medallion architecture. Architecture Leadership & Technical Guidance: Lead design reviews for new data products, integrations, and pipelines while providing architectural guidance on entity resolution, model design, cross-system key management, and system interoperability. Enterprise Data Strategy & Mentorship: Identify and document Systems of Record (SoR), Single Sources of Truth (SSoT), and Single Versions of Truth (SVoT) across domains while mentoring architects, engineers, and technical teams on enterprise data modeling and semantic architecture best practices. RequirementsEducation: Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field. Experience: Minimum of 8 years of experience in enterprise data architecture, information architecture, advanced data modeling, or related disciplines. Skills:Expertise designing enterprise data models across conceptual, logical, and implementation layers. Strong experience with domain-driven data modeling and business capability-based architecture. Deep understanding of Master Data Management (MDM), entity resolution, metadata management, and business glossary disciplines. Experience designing ontologies, taxonomies, semantic models, or knowledge representation frameworks in complex enterprise environments. Strong understanding of modern cloud data platforms and Lakehouse architectures, including Databricks or similar technologies. Experience partnering with governance, engineering, analytics, and architecture teams to implement scalable and governed data solutions. Excellent communication and stakeholder management skills with the ability to influence both technical and executive audiences. Certifications: Relevant cloud, data architecture, or governance certifications are a plus. Other: Ability to lead cross-functional initiatives, mentor technical teams, and align enterprise data strategy with long-term business objectives. Preferred QualificationsExperience with domain-driven design (DDD), enterprise architecture frameworks, or enterprise information governance programs. Familiarity with semantic and modeling standards such as ER modeling, UML, RDF, OWL, or SKOS. Experience supporting knowledge graph, semantic layer, or AI-ready data architecture initiatives. Exposure to Databricks architecture patterns for governed data assets, curated data layers, and reusable enterprise data products. Ability to bridge business strategy with practical architectural design across transactional, analytical, and integration ecosystems. Experience mentoring analysts, data engineers, and architects on enterprise data modeling best practices. Industry experience in legal services, financial services, or other highly regulated industries preferred.