Director of Development and Data Engineering
Python-first data engineering leader — building ETL architectures, workflow orchestration, and full-stack tools with Prefect, Databricks, and FastAPI.
Selected Work
Designed and implemented a data ingestion architecture using Prefect, Python, and Delta Lake — reducing ETL processing time from hours to minutes across multiple acquired companies.
83% reduction in ETL processing time; real-time business intelligence without growing the team.
Audited and consolidated 150+ scattered integrations using Azure Logic Apps and Functions into a structured monorepo, then built internal tooling to monitor and enforce data standards across pipelines.
30% reduction in integration failures; 25% fewer data errors through pipeline observability tooling.
Built an internal automation app using FastAPI, Django, and React, and implemented HR-led user provisioning via Azure AD — eliminating manual IT workflows across onboarding, offboarding, and asset tracking.
50+ hours per week in manual IT workload eliminated; significant reduction in support tickets.
About
I build data platforms and automation systems that compress hours of manual work into machine time — not shift the overhead somewhere else.
My work spans the full stack: ETL pipeline design and dbt transformations at the data layer, FastAPI and Django at the API layer, and React at the interface.
I lead data engineering teams with a focus on clear architecture, SDLC discipline, and software that gets more reliable as it scales.
What I Use
Blog
The idea that keeps shaping how I build software: design systems that remove support work instead of quietly generating more of it.
The stack I keep coming back to for data engineering, APIs, and full-stack work, and why I still like boring, dependable tools.
