Enterprise technology, data, and AI leader — 16+ years bridging hands-on architecture and end-to-end delivery.
I work at the intersection of enterprise data, AI, and technology operations — designing the platforms and governance that let organizations trust their data, then leading the delivery that gets those platforms into production and keeps them running.
My path here wasn’t linear by design — it was linear by necessity. I started as a Senior Web Integration Specialist wiring systems together by hand, moved into production support and root-cause analysis at Expedia, then spent over four years at Koch Technology Centre turning a global compliance-IT portfolio into a governed, automated operation. Aon is where the Master Data Management specialization sharpened — architecting Reltio data models and later leading the support organization that kept golden records trustworthy in production. Today, that full arc — hands-on technical depth plus enterprise-scale governance — is what lets me advise on and deliver technology, data, and AI initiatives without losing sight of the details that make or break a program.
The center of gravity is Master Data Management on Reltio — data modeling, golden records, match & merge, and the governance that keeps a dataset trustworthy years after go-live. Around that sits the broader enterprise stack I've operated in day to day: data analytics and reporting, IT consulting and digital transformation, managed IT and application operations, business process automation, and — more recently — applying generative and agentic AI to real operational workflows rather than treating it as a side project.
I don't believe good delivery depends on heroics under pressure. It depends on building the governance, the team structure, and the data foundations early enough that pressure rarely escalates into a crisis. That means clear KPIs and RAG reporting instead of status theatre, stewardship and ownership built into the data model instead of bolted on after an audit finding, and automation designed to remove repetitive work — never to remove accountability. I've led distributed onshore/offshore teams of 45+ across insurance, manufacturing, and investment domains, and the pattern holds regardless of industry: people who understand why a process exists follow it better than people who are just told to follow it.
Before proposing a platform or a framework, I want to understand the business problem it's solving — which stakeholders are affected, what "good" looks like operationally, and what happens if nothing changes. From there, the technology choice (an MDM platform, an automation workflow, an AI-assisted process) follows the problem rather than leading it. I'd rather ship a smaller, governed improvement that a team can maintain than a large platform nobody fully owns six months after launch.
See the complete timeline of roles, companies, and tenure — or explore the specific expertise areas I bring to an engagement.