Bringing Fortune 500 Visibility to the Middle Market
Mid-market companies faced Fortune 500 complexity without access to the specialized teams that typically solve it. We built the platform that bridged that gap, no data team required.
Data Engineer, Solution Architect, Problem Solver
Available NowFrom startup co-founder to Fortune 5 engineer -
crafting the solutions and systems teams rely on.
19 years building data platforms across startups and enterprise.
SELVR·Remote
OverlayAnalytics·Remote
Cigna·Remote
UnitedHealth Group·Remote
Elevance Health (formerly Anthem, Inc.)·Remote
Intelemedia Communications·Plano, TX
Santander Consumer USA, Inc.·Lewisville, TX
Mouser Electronics·Mansfield, TX
Real problems solved, real impact delivered.
Mid-market companies faced Fortune 500 complexity without access to the specialized teams that typically solve it. We built the platform that bridged that gap, no data team required.
A Teradata renewal cliff and a cloud mandate from leadership forced one of the country's largest health insurers to rebuild its data backbone. We migrated 100TB to GCP, retired $800K+ in annual licensing, and gave a 10,000-person data org the foundation it had been waiting for.
A PE-backed live commerce platform was carrying excess compute on a data operation that had been left to drift, while revenue was already declining and the gap was getting visible to leadership. I rescued the environment, collapsed 430 pipelines to 12, and pulled $480K of annual cost out of the structure.
Thoughts on data engineering, AI, and things I find interesting.
Rolling Copilot out to your engineers is the lowest-leverage AI move on the board. Three other rungs compound much harder, and most DE orgs are leaving them on the table.
Most pipeline YAML schemas grow into accidental domain-specific languages, with no spec, no design review, and a 2 a.m. on-call engineer debugging a templated `unless` block. The teams that escape design the language on purpose and treat the schema like a public API.