Chief Data Officer

Business Services | Chicago, New York, San Francisco & London

The Chief Data Officer will serve as the Firm’s executive leader responsible for treating data as a strategic business asset. The role‑holder will establish and operate an enterprise data governance and data management program, delivering trusted reporting and analytics, and partnering across Practice, Business Services, and Technology to improve client service, matter outcomes, operational efficiency, risk management, and profitability. The individual will balance business stewardship—including governance, operating model, and adoption—with technology enablement across platforms, architecture, engineering, and AI to ensure Firm data is accurate, secure, accessible, and usable.

Main responsibilities:

Data Strategy & Business Value:

• Define and execute the Firm-wide data strategy aligned to client service, practice growth, matter management, and financial performance
• Translate strategic objectives into a multi-year data roadmap covering governance, master/reference data, analytics, AI readiness, and self-service enablement
• Create and manage a portfolio of data products (e.g., Client 360, matter profitability, pricing intelligence, conflicts analytics) with clear owners and measurable outcomes

Business Data Governance (Operating Model):

• Establish an enterprise data governance model with clear decision rights, accountability, and operating cadence, including councils, stewardship networks, and escalation paths
• Define and enforce standards for data ownership, stewardship, business definitions (glossary), metadata/lineage, classification, and lifecycle/retention
• Ensure consistent definitions for core Firm concepts, such as client, matter, engagement, timekeeper, rate, fee arrangement, practice group, and office
• Enable governance that accelerates adoption while balancing controls with business agility and partner expectations

Data Management & Operations (Day-2 Excellence):

• Build and run an enterprise data management function spanning data quality, master/reference data, metadata management, and data issue remediation
• Implement data quality monitoring, controls, and remediation workflows with accountable stewards and measurable quality thresholds for critical data elements
• Operationalize Master Data Management (MDM) and hierarchies (e.g., client/matter, timekeeper, and practice/industry taxonomy)
• Establish a data services catalog with SLAs, incident/problem management, and operational reporting for reliability and trust
• Strengthen data integrity across critical processes, including conflicts checks, new matter intake, time entry, billing, collections, and reporting

Data Architecture, Platforms & Engineering (Technology Leadership):

• Co-own with Technology Leadership the enterprise data platform strategy covering warehouse/lakehouse capabilities and integration patterns across core Firm systems
• Lead delivery of data ingestion, transformation, orchestration, and API enablement to support scalable analytics and operational reporting
• Develop a governed semantic layer and metrics framework to provide consistent, reusable measures (e.g., realization, margin, and utilization)
• Embed engineering best practices, including observability, automated testing, CI/CD for data pipelines, and resilient operations

Analytics, Insights & Decision Enablement:

• Deliver trusted reporting and analytics across Practice and Business Services, prioritizing partner-facing insights that drive action
• Enable data sets for analytics on matter profitability and realization, pricing and rate management, utilization and capacity planning, and client/industry insights for Business Development (BD)
• Champion self-service analytics with guardrails using certified datasets, governed metrics, user enablement, and training
• Create an insights operating model that moves beyond dashboards to measurable decisions and outcomes

AI & Data Readiness (Responsible Enablement):

• Partner with Innovation, Knowledge Management, Technology, Functional Leaders, and Practice Leadership to enable responsible AI through high-quality, well-governed data
• Define data readiness standards for AI use…