I started in data warehouses. A city government data team, 2014: SSIS packages, month-end reports, and the slow realization that most organizations do not have a data problem. They have a trust problem.
Twelve years later, the resume says I led enterprise reporting at a healthcare payer, architected the BI platform that carried a supply chain company through a merger into a multi-billion-dollar business, modernized financial data for one of the largest apartment developers in the country, and built the revenue intelligence platform a $1B software company uses to run board meetings.
What it actually means: I sit where data meets decisions. Sales, Finance, Marketing, Operations. I have watched forecasts get argued about in rooms where nobody could say why the number moved, and I have built the systems that ended those arguments. Not with prettier charts. With provenance: numbers that carry their own chain of custody, so leaders stop debating the data and start deciding with it.
The craft changed along the way. It used to be SQL, star schemas, and refresh windows. It still is, but now the frontier is AI: LLM-assisted analytics, agentic workflows that act instead of waiting to be read, and MCP integrations that connect models to enterprise data safely. I write about that shift and I build working demos of it, because claims without mechanisms are just marketing.
These days I work from Sarasota, Florida. I take on a small number of consulting engagements, I am open to the right leadership seat, and I am building toward ventures of my own. I care about work that holds up under scrutiny and about giving back more than I take.