Lead Product Owner - Data Analytics

Job Posting:

Since 1953, Ferguson has been a source of quality supplies for a variety of industries. Together We Build Better infrastructure, better homes and better businesses. We exist to make our customers’ complex projects simple, successful, and sustainable. We proactively solve problems, adapt and grow to continuously serve our customers, communities and each other. Ferguson, a Fortune 500 company, is proud to provide best-in-class products, service and capabilities across the following industries: Commercial/Mechanical, Facilities Supply, Fire and Fabrication, HVAC, Industrial, Residential Trade, Residential Building and Remodel, Waterworks and Residential Digital Commerce. Ferguson has approximately 36,000 associates across 1,700 locations. Ferguson is a community of proud associates who operate with the shared purpose of building something meaningful. You will build a career that you are proud of, at a company you can believe in.

As a Lead Product Owner on the Boundary Applications and Analytics team, you will own the strategy, vision, and roadmap for Ferguson’s Decision Support Center space – the trusted source for accurate and interactive Enterprise and Operational reporting. This role operates at the intersection of technology and business functions, requiring close partnership with Finance to define, prioritize, and deliver solutions that supports the company’s “one source of truth” strategy. This role is focused on understanding the needs of internal business customers, deriving business value, offering thought leadership throughout the software delivery lifecycle, and leading technical teams to deliver large-scale projects with speed and quality. You will be a technology partner, relentlessly building and advocating for the customer while simultaneously listening and negotiating with business collaborators across the company. You will help craft a comprehensive backlog and design a thoughtful roadmap for execution of Ferguson’s vision, ensuring each report is precise, reliable, and timely. The ideal candidate brings experience leading Data Analytics teams in fast‑paced environments, thrives amid ambiguity, and takes direct accountability for delivering measurable business value.