Legal Business Data Architect

King & Spalding is a leading global law firm with a commitment to excellence, innovation, and the seamless delivery of legal services. We harness innovative technology and exceptional talent to meet the complex needs of our clients in a fast-paced and dynamic legal landscape.

We are seeking a highly skilled and experienced Data Architect to join our dynamic legal organization. This role uniquely blends business architecture and data engineering, with a primary focus on supporting internal operations while also enabling transformational technology solutions for our legal practice groups. The ideal candidate will bridge technical expertise with legal domain knowledge, ensuring our data architecture aligns with both business operations and strategic client service objectives.

This role offers a unique opportunity to build and optimize the data architecture that powers critical business functions across marketing, finance, professional development, and legal practice, while also enabling advanced analytics and AI capabilities.

KEY RESPONSIBILITIES:

Business Architecture & Data Strategy

• Develop and Maintain Business Architecture: Create and maintain business architecture models that support the organization's strategic objectives, with specific emphasis on legal operations and business functions.
• Data Strategy & Governance: Define and implement a comprehensive data strategy that aligns with firm-wide business goals and facilitates effective data governance across all internal departments.
• Data Flow Management: Design and manage data flows across the organization, ensuring data integrity, availability, and seamless integration between practice management, financial, HR, marketing, professional development, and operational systems.
• Data Engineering: Implement data engineering practices to build robust data pipelines, ensuring efficient processing and transformation of structured and unstructured legal and business data.
• Cross-Departmental Collaboration: Work closely with stakeholders across IT, legal operations, finance, HR, marketing, business development, and professional development to understand requirements and translate them into effective data solutions.
• Standards and Best Practices: Establish and enforce data architecture standards and best practices, ensuring consistency and quality across enterprise systems.
• Analytics Infrastructure: Develop and maintain analytics platforms that enable data-driven decision-making for business operations, resource planning, and strategic initiatives.

Legal Practice Group Support & AI Integration

• Attorney Enablement: Liaise with attorneys and practice groups to understand their data and technology needs, translating requirements into practical data architecture and AI-driven solutions.
• Legal Technology Integration: Active in the assessment, benchmarking, and deployment of legal technologies (AI, document automation, contract analysis, e-discovery, and research tools) that leverage the firm's data architecture.
• Technology Assessment: May conduct research on legal technology trends and emerging platforms and provide support to pilot programs for practice-specific applications and client-facing technology solutions.
• Training & Documentation: Assist the enablement and training teams with instructions and deliverables to attorneys and staff. Maintain thorough documentation of prototypes, experiments, design specifications, and methodologies.

Enterprise-Wide Responsibilities

• Risk Management: Identify and mitigate data-related risks, ensuring compliance with legal industry regulations, privacy standards (attorney-client privilege, confidentiality), and security requirements.
• Tools and Technology Evaluation: Evaluate and recommend tools and technologies that support the data architecture framework, with consideration for legal-specific platforms and vendor relations.
• Performance Measurement: Measure impact and ROI for data and technology projects; establish metrics for adoption and effectiveness.

QUALIFICATIONS:

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or related field. JD, MBA, or Master's in Library Science (MLS) strongly preferred.
• 5+ years of proven experience in business data architecture and data engineering, with demonstrated experience in a law firm or professional