Program Director, Data & Analytics

Prologis•Las Vegas, NV

1d•Hybrid

About The Position

As Program Director of Data & Analytics, you will help the organization turn data into action in an AI-first world. You will connect strategy to execution across Data Engineering, Analytics Engineering, and Data Visualization, ensuring teams deliver trusted, scalable data products that enable smarter, faster decisions. AI will be foundational to how you operate, as you identify opportunities to apply automation and agent-based workflows to improve efficiency and accelerate insight generation. You will also drive strong execution by aligning priorities, managing capacity, guiding teams toward shared outcomes, and maintaining momentum as priorities evolve. You will oversee budgets and investments to support the highest-impact work, while shaping how the business experiences data through intuitive, scalable, self-service analytics. In close partnership with leaders, stakeholders, and external partners, you will help evolve the operating model so the organization can scale and deliver increasing value over time.

Requirements

10+ years of experience in Data, Analytics, or Technology roles
5+ years of leadership experience across cross-functional or delivery-focused organizations
Proven experience driving AI, automation, or advanced analytics adoption within teams or organizations
Proven experience managing planning cycles, OKRs, and delivery in complex environments
Strong understanding of modern data and analytics ecosystems (e.g., SQL, BI tools, data platforms)
Proven ownership of end-to-end financial management across multiple capabilities and cost centers, including budgeting, forecasting, investment prioritization, and cost optimization
Proven experience managing external vendors, consulting partners, and geographically dispersed teams
Demonstrated ability to operate across multiple teams and influence without direct authority
Excellent communication and stakeholder management skills

Nice To Haves

Experience incorporating AI, automation, or agent-based workflows into analytics or operations
Experience working within Data & Analytics organizations (Data Engineering, Analytics Engineering, BI/Visualization)
Familiarity with platforms such as Snowflake and enterprise BI tools
Experience incorporating AI, automation, or agent-based workflows into analytics or operations
Experience with product or pod-based delivery models, including working with globally distributed and remote teams
Strong change management mindset and comfort operating in evolving environments
Demonstrate willingness and capability to leverage emerging technology, automation, and AI tools to improve efficiency, quality, and speed.
Exercises sound judgment, creative thinking, and accountability for outcomes.

Responsibilities

Drive AI-first adoption across Data & Analytics, identifying and implementing opportunities for AI, automation, and agent-based workflows to transform analytics and team operations
Run operating rhythms (planning, OKRs, delivery tracking, reporting) to drive alignment, accountability, and transparency across Data & Analytics, ensuring OKRs are clearly defined, aligned across teams, and tracked with measurable outcomes
Monitor delivery health, proactively identify risks, bottlenecks, and dependencies, and drive continuous improvement in execution and team performance
Coordinate resource allocation and prioritization across teams to balance demand, capacity, and strategic priorities, including managing trade-offs when demand exceeds capacity
Own financial management across the function, including budgets and forecasts spanning multiple capabilities and cost centers, ensuring investments are aligned to strategic priorities and maximize ROI
Manage vendor partnerships and external resources to ensure strong performance, accountability, and cost efficiency
Lead the Data Visualization capability, defining its evolution in an AI-first world and ensuring delivery of trustworthy, scalable, self-service analytics aligned with AI-enabled insights, including oversight of tools such as Sigma, Tableau, and ESRI
Promote data-driven decision-making and drive adoption of analytics through governance, communication, and change leadership
Ensure analytics products and services are reliable, secure, well-documented, and supported through strong production support, issue resolution, and continuous enhancement practices