Job Description & Details
This is a heavy-hitting digital procurement leadership role where you won't just manage categories, you'll completely overhaul how the entire organization leverages sourcing tech and data. If you enjoy sitting at the intersection of supply chain, IT architecture, and AI enablement to actually fix broken enterprise workflows, this gig in Richardson is worth a serious look.
What You'll Actually Be Doing
You'll spend your days acting as the ultimate bridge between stubborn procurement teams, complex IT backends, and data science squads. Expect to lead massive system enhancements, clean up messy master data sets that nobody wants to touch, and push the envelope on AI-driven spend analytics. You'll be mapping out end-to-end processes, figuring out why sourcing cycle times are dragging, and driving genuine change management so your tools actually get used instead of ignored.
The Core Tech Stack
You need deep fluency in enterprise procurement platforms like SAP Ariba, Coupa, or Oracle, alongside a strong grasp of master data management frameworks. Because this role leans hard into modern tech, you'll also be expected to champion AI/ML use cases like predictive spend analytics and supplier risk modeling. Knowing your way around visualization tools like Power BI or Tableau to build single sources of truth is non-negotiable.
Interview Expectations
Be ready for the hiring manager to press you on a time you had to herd cats across IT and business units to push a major software implementation across the finish line. They want to know how you handle technical pushback from old-school buyers who hate new software. Another favorite will be walking through your exact methodology for cleaning up dirty supplier data and establishing automated governance rules that actually stick.
Application Advice
Make sure your resume doesn't just read like a list of traditional contract negotiations. You need to heavily spotlight keywords like 'Master Data Management', 'eSourcing platforms', 'Process Re-engineering', and 'AI/ML procurement enablement' to clear the automated ATS filters. Emphasize measurable outcomes where your system integrations or data governance frameworks actually moved the needle on cycle times or cost savings.