About
I started in recruiting. Now I build the platforms recruiting runs on.

I spent the first half of my career in technical recruiting, covering engineering and data roles in Berlin, San Francisco, and Chicago, and kept ending up on the systems side of it. I ran a Greenhouse implementation, scoped Workday Recruiting business processes, instrumented funnels, and built the headcount models recruiting leaders argued over.
That pulled me into analytics. At a 23,000-employee healthcare enterprise I built the People Analytics function from scratch, governed a very large Workday reporting estate, chaired the committee that set conventions for 80+ analysts, and built forecasting models that changed hiring plans before capacity gaps showed up in revenue.
Then the tooling changed, and the thing I could do about it changed too. Today I work as an engineer: I architect and ship the platforms: governed HR data warehouses, integrations, agentic systems in production, rather than filing tickets for someone else to. My identity in one line is builder-in-residence for People Technology. I don't adopt tools; I build the infrastructure other people and other agents build on.
I work unusually publicly: decisions narrated in project channels, misfires owned openly, documentation written so the next person, or the next agent, can pick up an in-flight epic. That habit is why the work compounds instead of stranding with me.
How I work
Governance is a build phase, not a cleanup phase
HR data is the most sensitive data a company holds. Row-level access, masking, and sensitivity classification belong in the first commits, gating every merge after. Retrofitting them costs more and protects less.
Agents are consumers, so build for them
If a system is only legible to humans, agent adoption stalls at a demo. Catalogs, machine-readable tiers, explicit temporal semantics, and automated findability checks are what make certified data usable by something that isn't a person.
Speed comes from gates, not from skipping them
Generation is cheap now; judgment is the scarce resource. Orchestrated agents with narrow scopes and mandatory adversarial review ship faster than a single unreviewed thread, and the output survives contact with production.
Recruiting taught me the requirements half
Ten years inside talent processes means I know what a recruiting funnel metric actually means before I model it, and what an HR leader will do with the number once they have it. Most data problems in People are definition problems.
Skills
HRIS & Platforms
- Workday HCM (advanced reporting, calculated fields, Recruiting)
- Greenhouse
- Databricks (Unity Catalog, Lakeflow)
- Airtable
- Tableau
- BigQuery
- Google Cloud
Engineering & AI
- SQL
- Python
- Data pipelines & integrations
- CI/CD
- HR data privacy & governance
- AI agent orchestration
Education
Mercer University
BBA, Sports Business Management · 2016 · Macon, GA