Director, Data & AI Business Architecture

Introduction

At Gallagher Benefit Services, you’re a trusted partner to organizations navigating some of their most important people decisions. We help clients build better workplaces, where people feel supported, empowered, and inspired to thrive. Whether it’s shaping benefit strategies, designing wellbeing programs, or advising on workforce challenges, the work you do here creates meaningful change for businesses and the people who power them.

We’re a community of bold explorers, trusted experts, and compassionate partners; working side by side to solve problems, and shape the future of work. Here, curiosity is encouraged, collaboration is second nature, and your ideas have room to grow. If you’re looking for a place where your contribution matters and where you can help build a better world of work;

think of Gallagher.

The Director, Data & AI Business Architecture leads business data architecture for the division. Accountable for ensuring data is designed to support AI and analytics ablishes standards, models, and governance that enable consistent, reusable data across regions and business lines. Operates through a federated model with a lean central team and broad influence across delivery teams.

Impact – This role enables AI by ensuring the right data foundation is in place. Through strong standards and influence across a federated model, it drives consistency, reduces rework, and allows the division to scale analytics and AI effectively.

Division Data Architecture Ownership

• Define and own business data models across the division.
• Establish domains, entities, facts, and dimensions aligned to business processes.
• Create a consistent semantic layer to support reporting and AI use cases.

AI Enablement Through Data Design

• Ensure data structures are built for AI from the start.
• Define standards for feature‑ready, reusable datasets.
• Partner with AI and engineering teams to reduce time to deploy use cases.

Federated Operating Model

• Lead through influence across distributed teams in regions and business units.
• Establish standards adopted by product, engineering, and analytics teams.
• Drive alignment without direct control of all resources.

Global Consistency

• Set data design standards across US, EMEA, and APAC.
• Balance global consistency with regional requirements.
• Enable reuse of data across markets and solutions.

Business Performance Alignment

• Align data design to key business metrics such as revenue, pipeline, utilization, and client outcomes.
• Eliminate conflicting definitions across the division.
• Enable consistent, trusted reporting and decision‑making.

Governance & Data Quality

• Define ownership, lineage, and quality expectations.
• Establish trust levels for data used in analytics and AI.
• Ensure traceability from source systems to outputs.

Operating Model & Team Structure

• Lean central team within the CDO organization.
• Direct team: 2–3 resources (architecture, modeling, or data design leads).
• Broader impact delivered through:
• Business‑aligned data teams
• Engineering and analytics teams
• AI and product teams

• 12–15+ years in data architecture, data modeling, or analytics.
• Experience designing data for AI and advanced analytics use cases.
• Strong understanding of business processes in complex organizations.
• Experience operating in a federated or matrixed environment.
• Proven ability to drive standards through influence.
• Strong executive communication skills.

• Experience in professional services, insurance, or financial services.
• Experience working across global teams.
• Familiarity with governance and regulatory environments.

• Business data modeling and domain design
• AI data readiness and standardization
• Federated operating model leadership
• Data governance and quality
• Executive communication
• Cross‑functional influence

We offer a competitive and comprehensive compensation package. The base salary range represents the anticipated low end and high end of the range for this position. The actual compensation will be influenced by a wide range of factors including, but not limited to, previous experience, education, pay market/geography,…