Head of Data

Corporate:

Light & Wonder’s corporate team is comprised of incredible talent that works across the enterprise, defying boundaries to provide essential services in an extraordinary manner to ensure the success of the organization and the well-being of employees.

Position Summary

The Head of Data is a critical, highly visible leadership role at the heart of Light & Wonder's AI transformation. Reporting directly to the Chief Strategy Officer, this leader will build L&W's centralized data hub, establishing the infrastructure, master data management, governance, and data science capability that the enterprise AI agenda depends on. This role partners directly with the Executive Leadership Team, business unit leaders, Finance, Operations, and Technology to ensure data becomes a defensible source of competitive advantage and a measurable driver of business value.

Light & Wonder has embarked on an ambitious AI-enabled transformation, and the Head of Data will serve as a core architect of that journey, translating L&W's data ambition into infrastructure, capability, and outcomes that directly support the enterprise AI AEBITDA agenda. This is an executive level role with significant scope, significant visibility and significant impact.

Primary Roles and Responsibilities Include:

Lead the Build of L&W's Centralized Data Function

• Stand up L&W's centralized data hub, including infrastructure, master data management, governance, data engineering, analytics engineering, and data science capability.

• Define and operate the hub-and-spoke operating model that pairs centralized standards with embedded data partnership across business units and functions.

• Hire, onboard, and develop the full data hub team, building a high-performing organization with a strong talent bar and low attrition.

Develop and Execute the Multi-Year Data Strategy

• Develop a multi-year data roadmap covering infrastructure, master data management, governance, and AI-aligned use-case sequencing, endorsed by the Executive Leadership Team and integrated into the broader AI transformation plan.

• Translate L&W's enterprise strategy and AI ambitions into a sequenced, executable data investment plan with clear value, timing, and accountability.

• Make architectural and platform decisions that establish Snowflake-as-source-of-truth, modern data tooling, and governance standards across the enterprise.

Drive Measurable Business Value

• Deliver an early, fully shipped, financially-validated win that demonstrates the value of the data function, visible to leadership, signed off by Finance, and meaningful in dollar impact.

• Stand up data infrastructure that materially supports Finance and Operations in achieving their AI AEBITDA targets, including documented data dictionaries, lineage, and shared definitions.

• Ensure the data infrastructure built and operated by this role drives a meaningful share of L&W's enterprise AI AEBITDA target by 2028, with Finance attestation.

• Build and deliver an R&D Intelligence Layer to support portfolio and game development decision-making, partnering closely with the Head of Product.

Establish Enterprise Data Governance and Trust

• Establish and operate enterprise data governance, including policies, stewardship roles, data domains, decision rights, and an executive Data Council. Governance must drive measurable adherence and behavior change, not just policy documentation.

• Ensure data quality, security, regulatory compliance, and AI-readiness across critical data domains.

• Build the trust, transparency, and shared definitions that allow data to be confidently used in decisions across Finance, Operations, and the business units.

Executive Leadership Collaboration and Strategic Influence

• Serve as a trusted partner to the Chief Strategy Officer, Executive Leadership Team, and Board on data and AI priorities.

• Build coalitions with peer leaders across Technology, Finance, Operations, and the business units, driving alignment without relying on hierarchical authority.

• Prepare and deliver executive-level communications, insights, and recommendations that translate data and AI strategy into business outcomes.

Qualifications

• Significant experience leading data, analytics, or data engineering organizations at the VP, SVP, or Chief Data Officer level.

• Track record of building data capability in technically compl