Senior Data Engineer | Minneapolis, MN
20 years of learning by doing
University of Saint Thomas - Psychology major with Business minor
What I learned: Pattern recognition, research methods, statistics, stakeholder management
Why it matters: Data engineering is pattern recognition. Requirements gathering is stakeholder management.
U.S. Bank - Bond Operations Processor
Entry-level back-office role processing compliance paperwork.
What happened: I automated my own job with VBA. Realized I loved building systems more than following processes.
Result: Got promoted to Programming Analyst within a year.
The Pattern: VBA → VB.NET → SQL
Learning method: Build something → Break it → Fix it → Repeat
Companies: Best Buy, Rust Consulting, Target
What I built: Internal tools, data exchange processes, reporting systems
Pattern established: Join company → Find manual process → Automate it → Move to next challenge
The Shift: From application development to data pipelines
Realization: I'm better at moving data than building UIs
USCG LLC: First exposure to AWS vs GCP comparison
1upHealth: Healthcare data + AWS infrastructure
Learning method: Same as always - build, break, fix, ship
Dartmouth Applied Data Science Certificate
After 15 years of self-teaching, finally got academic credentials.
Why it mattered: Proved I could explain what I'd been doing for years.
Augeo: SQL Server → AWS RDS/EC2 migration
Led zero-downtime migration. Same experimental approach - test in dev, validate in staging, execute in production.
Deloitte - Senior Consultant
70% efficiency gain using Python + AI automation
November 2022: Started using ChatGPT (first week of release)
Impact: 10x productivity increase
How I use it:
Reality: I'm an AI orchestrator now, not a traditional coder
xBrezzo Consulting: Built family law case management system
Tech stack: Lovable (AI platform), Supabase, Claude Code
Method: Describe what's needed → AI generates code → Test → Iterate
Result: Working production system in weeks, not months
Psychology research is about finding patterns in behavior. Data engineering is finding patterns in data.
Understanding stakeholder needs → translating to technical specs. Same skill as therapy → treatment plans.
Psychology: Hypothesis → Test → Analyze → Iterate
My approach: Build → Test → Fix → Ship
From bar owners to state government officials - same communication principles.
I'm not a traditional engineer:
What I can do:
Senior Data Engineer | Minneapolis, MN
20 years of learning by doing
University of Saint Thomas - Psychology major with Business minor
What I learned: Pattern recognition, research methods, statistics, stakeholder management
Why it matters: Data engineering is pattern recognition. Requirements gathering is stakeholder management.
U.S. Bank - Bond Operations Processor
Entry-level back-office role processing compliance paperwork.
What happened: I automated my own job with VBA. Realized I loved building systems more than following processes.
Result: Got promoted to Programming Analyst within a year.
The Pattern: VBA → VB.NET → SQL
Learning method: Build something → Break it → Fix it → Repeat
Companies: Best Buy, Rust Consulting, Target
What I built: Internal tools, data exchange processes, reporting systems
Pattern established: Join company → Find manual process → Automate it → Move to next challenge
The Shift: From application development to data pipelines
Realization: I'm better at moving data than building UIs
USCG LLC: First exposure to AWS vs GCP comparison
1upHealth: Healthcare data + AWS infrastructure
Learning method: Same as always - build, break, fix, ship
Dartmouth Applied Data Science Certificate
After 15 years of self-teaching, finally got academic credentials.
Why it mattered: Proved I could explain what I'd been doing for years.
Augeo: SQL Server → AWS RDS/EC2 migration
Led zero-downtime migration. Same experimental approach - test in dev, validate in staging, execute in production.
Deloitte - Senior Consultant
70% efficiency gain using Python + AI automation
November 2022: Started using ChatGPT (first week of release)
Impact: 10x productivity increase
How I use it:
Reality: I'm an AI orchestrator now, not a traditional coder
xBrezzo Consulting: Built family law case management system
Tech stack: Lovable (AI platform), Supabase, Claude Code
Method: Describe what's needed → AI generates code → Test → Iterate
Result: Working production system in weeks, not months
Psychology research is about finding patterns in behavior. Data engineering is finding patterns in data.
Understanding stakeholder needs → translating to technical specs. Same skill as therapy → treatment plans.
Psychology: Hypothesis → Test → Analyze → Iterate
My approach: Build → Test → Fix → Ship
From bar owners to state government officials - same communication principles.
I'm not a traditional engineer:
What I can do:
Judge me on outcomes, not process.