Player-coach data engineer and product leader with a track record of changing the slope of the growth curve. Partner and early employee at three companies: one acquired, one scaled from $15M to $100M ARR, one built from zero to a bank-grade analytics platform.
at Autobooks
year over year
Autobooks Hub
Partner at a Detroit fintech building invoicing and payment processing for SMBs via online banking.
- Architected Autobooks Hub — an in-browser analytics platform consolidating Receivables, Capital, Accounting, and platform events into a single interface
- Designed the full data pipeline: SQL Server → Azure Functions → Arrow IPC → Parquet → DuckDB-WASM, enabling instant client-side queries with zero server round-trips
- Built a Claude-powered AI assistant that generates SQL from natural language; queries run entirely client-side, data never leaves the browser
- Implemented a 122-permission scoped access system (verb:resource@scope) managed through Auth0 JWT tokens
- Designed a Segment Protocols tracking plan with 150+ events across the full Hub user journey
Owned product analytics and growth engineering, building the data infrastructure to measure and optimize the SMB onboarding funnel.
- Drove 3x+ acquired users, 5x+ active users, and 10x+ gross merchandise volume YoY
- Integrated Autobooks with Segment CDP, establishing the event tracking foundation that now powers Hub analytics
Partner — joined at $15M ARR, departed at $100M ARR. Owned the full marketing automation stack as both engineer and power user.
- Built complex multi-channel automation workflows processing millions of emails daily
- Created developer education content including API tutorials with Serverless, AWS Lambda, and IoT hardware
Early employee at a referral marketing platform; built and scaled growth and marketing through acquisition.
- Integrated referral tracking with Salesforce, SendGrid, MailChimp, PayPal, and Dwolla
- Owned the full marketing data stack: attribution, analytics, and automation
SaaS platform analyzing environmental and operational data to predict retail location revenue performance.
- Built data pipelines ingesting from Google Places, Yelp, Foursquare, Facebook, and weather APIs into a unified analytics engine
"I can point to the chart and say — see where it changed from up and to the right to UP AND TO THE RIGHT? I did that."
Michigan State University
The Brandery — Accelerator, Alumni
i3 Detroit — Hackerspace, Member