We are seeking a Data Architect to define and advance the enterprise data architecture that underpins our business, analytics, and AI strategy. This role reports to Director of Data Platform & Engineering and is responsible for shaping how the organization models core business concepts, establishing shared data meaning across domains, and creating a scalable semantic foundation for data interoperability and reuse.

This role requires deep expertise in enterprise data modeling, domain-oriented information architecture, and ontology design. They will partner with business and technology leaders to create durable, business-aligned models that improve consistency, governance, discoverability, and decision-making across the enterprise.

• Define and govern the enterprise's conceptual, logical, and canonical data architecture.
• Lead the development of domain models that reflect core business entities, relationships, processes, and events across major functional areas.
• Define and govern the metadata architecture: active metadata strategy, data catalog integration (Unity Catalog, Alation, Collibra, or equivalent), and lineage representation across pipeline and model layers.
• Lead technical design reviews for new data products, pipelines, and integrations. Provide architectural guidance on model design, entity resolution, and cross-system key management.
• Identify and document the System of Record (SoR), Single Source of Truth (SSoT), and Single Version of Truth (SVoT) for each entity within each domain, and govern the distinction between them across the Medallion architecture.
• Partner with data governance, engineering, analytics, and architecture teams to ensure models are implemented in a governed and practical way.
• Enable the implementation of enterprise models within modern cloud and Lakehouse platforms, including Databricks, with appropriate governance and reuse.
• Design and evolve ontologies, taxonomies, and semantic models that support interoperability, metadata, analytics, and AI initiatives.
• Advise leadership and delivery teams on target-state data architecture, domain ownership, and long-term information strategy.
• Mentor architects, modelers, and senior technical teams in best practices for enterprise data and semantic architecture.
• Conduct a structured audit of existing data models, domain definitions, and any nascent ontology work, producing a gap assessment and prioritized roadmap.
• Publish a canonical domain map to serve as the authoritative list of data domains, their bounded contexts, primary entities, and system-of-record mappings.

Salaries vary by location and are based on numerous factors, including, but not limited to, the relevant market, skills, experience, and education of the selected candidate. If an estimated salary range for this role is available, it will be provided in our Target Salary Range section. Our compensation package also includes bonus eligibility and a comprehensive benefits program. Benefits information can be found atSidley.com/Benefits.

To perform this job successfully, an individual must be able to perform the Duties and Responsibilities (Duties) above satisfactorily and meet the requirements below. The requirements listed below are representative of the minimum knowledge, skill, and/or ability required. Reasonable accommodations will be made to enable individuals with disabilities to perform the essential functions of the job. If you need such an accommodation, please email sidleytalentacquisition@sidley.com (current employees should contact Human Resources). 

Education and/or Experience:

Required:

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
• A minimum of 8 years of experience in data architecture, enterprise information architecture, or advanced data modeling roles.
• Proven success designing enterprise data models across conceptual, logical, and implementation layers.
• Strong expertise in domain-driven data modeling and structuring information around business capabilities and ownership boundaries.
• Deep understanding of MDM and entity resolution to link key entities across data sources.
• Experience developing ontologies, taxonomies, semantic models, or knowledge representation frameworks in complex enterprise environments.
• Strong understanding of data governance, metadata management, master data, and business glossary disciplines.
• Experience working with modern cloud data platforms; familiarity with Databricks or similar Lakehouse architectures is strongly preferred.
• Excellent executive communication skills, with the ability to influence technical and business stakeholders alike.

Preferred:

• Experience with domain-driven design, enterprise architecture frameworks, or 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, including architecture patterns for governed data assets, curated data layers, and reusable enterprise data products.
• Ability to connect business strategy with practical architectural design across transactional, analytical, and integration landscapes.
• Experience mentoring analysts, data engineers and other architects on data modeling best practices
• Industry experience in legal or financial services a plus.

Other Skills and Abilities:

The following will also be required of the successful candidate:

• Strong organizational skills
• Strong attention to detail
• Good judgment
• Strong interpersonal communication skills
• Strong analytical and problem-solving skills
• Able to work harmoniously and effectively with others
• Able to preserve confidentiality and exercise discretion
• Able to work under pressure
• Able to manage multiple projects with competing deadlines and priorities

Sidley Austin LLP is an Equal Opportunity Employer

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