Built by a practitioner.
One engineer, end to end.
LucidDataMind is a data engineering and intelligence practice: one senior engineer — 20 years inside enterprise data operations — working with a fleet of AI agents I built. You work with me directly; the agents are why one person ships like a team. No layers of account managers. No junior handoffs. The person who scopes the work is the person who builds it.
Two decades of
real engineering
I started in enterprise data, long before “data engineering” had a name. I designed and deployed 200+ data integration solutions across 15+ integrated systems. POS, warehouse management, ecommerce, loyalty, ERP, general ledger — every system that mattered ran through those pipelines.
I build full Microsoft Fabric lakehouse modernizations — Loop automation for Bronze ingestion, Materialized Lake Views for Silver transformation, pipeline-driven Gold with a lakehouse semantic model and Data Agents.
LucidDataMind is where that experience meets independent practice. The same rigor, the same delivery standards — without the Big 4 overhead or the agency markup.
200+
Data integration solutions designed and deployed at enterprise scale
15+
Integrated systems — POS, WMS, ERP, loyalty, ecommerce, GL
I build from
where you are
Every company is somewhere on the data maturity curve. Some are running production workloads on SQL Server and SSIS that have been reliable for a decade. Some are mid-migration to the cloud. Some are starting from scratch. None of those starting points are wrong.
I assess where you are, identify where the highest-value improvements live, and build from there. Sometimes that’s a full Fabric lakehouse. Sometimes it’s a single pipeline that saves 20 hours a week. The right scope is the one that delivers measurable value fastest.
The methodology is always the same: medallion architecture, clean separation of concerns, production-grade code, and documentation that lets your team maintain what I build after I leave.
Twenty years of judgment.
A new kind of leverage.
The interesting question isn’t whether AI can build software. It’s what happens when someone who spent two decades architecting enterprise data systems directs it — knowing what to build, what to reject, and what standard the output must meet before it ships.
That’s the practice here. I work in rigorous, structured exchanges with frontier AI: I set the architecture, the constraints, and the acceptance bar. The AI executes at a pace no team can match. And nothing ships until it survives review — including independent AI reviewers whose only assignment is to play the skeptical buyer and try to break what was built. Every engagement runs the same discipline: audit before edit, evidence before claims, a gate before anything ships.
The result is enterprise-grade delivery from a single senior engineer — not because the work is smaller, but because the leverage is different. The proof isn’t this paragraph. It’s the work.
Dan Tweedie
Kirkwood, Missouri · DMT@LucidDataMind.com