About
Technologist, futurist, data purist.
I lead with geography. Almost everything an organization tracks happens somewhere — and that shared location is the thread I use to connect the systems they already have, and make sense of it all.
The short version
Most teams don’t need more data. They need it to speak the same language.
My work lives at the seams between systems — the places where a SharePoint list, an ArcGIS layer, a road network, and a labor-market dataset all describe the same reality but never quite meet. I build the bridges: geospatial analytics that turn location into decisions, automations that erase manual handoffs, and custom tooling that fuses disparate sources into one dependable system.
I care about doing it honestly — results that are reproducible, physically sensible, and resilient to the messy reality of real organizational data. The goal is never a clever demo. It’s a connected source of truth that people can act on, long after I’ve handed it over.
How I work
Principles earned the hard way — on real data, not in theory.
Run it, don’t just read it
The most expensive defects don’t show up in code review — they surface the moment a tool meets real data. I budget for iterative execution on representative datasets.
Verify against primary sources
Behavior gets confirmed against the vendor’s own documentation, not memory. Several of my best fixes came straight from reading the docs everyone else skips.
Own the data structures
The recurring source of fragility is the input. Copying messy sources into a clean representation I control removes whole classes of bugs at once.
Prevent silent wrong answers first
A crash gets noticed; a plausible-but-wrong result feeds a bad decision. I design against the quiet failures before the loud ones.
Build for the messy reality
Joins, blank parameters, mixed coordinate systems, nested layers — production data is never clean, so the tool handles all of it by default.
Make it portable and reusable
Self-contained, shareable, zero-dependency where possible — so the work keeps running on someone else’s machine, in another region, a year from now.
Toolkit
The stack I reach for.
Geospatial
Arcade
arcpy
Network Analyst
StreetMap Premium
H3 hex grids
Automation
Engineering
Python
NumPy
Data modeling
HTML / CSS
Git & GitHub
Domains
Credentials · a live roadmap
Earned, in progress, and queued.
I treat my own development like the systems I build — transparent and versioned. Here’s exactly where my credentials stand today, and what’s next. This board updates as each one lands.
Building the credential set deliberately — industry-recognized certifications alongside continued learning.
Built for what's next
Four traits I sharpen every day: ALIC.
Technology keeps moving — the AI era most of all. These are the traits that keep me valuable through every shift, and they're trained, not assumed.
Adaptability
New platform, new dataset, new constraint — I re-orient fast and deliver in the environment that exists, not the one I'd prefer.
Learning
Always a current certification track, a primary source, or a new tool under my hands. Staying current isn't a phase; it's the practice.
Ideation
Seeing the connection others miss — between systems, datasets, and disciplines — and turning it into a concrete, buildable concept.
Change
Ideas are cheap; enacted change is rare. I carry solutions through adoption — the tool used, the workflow switched, the decision made.
Let’s connect your systems.
If your data is scattered across tools that don’t talk to each other, that’s exactly the kind of problem I want to hear about.