What Thomas does
I design and build the data systems your production runs on. Clear architecture, AWS-native, deployed, monitored, and documented so your team can own it.
Data is the core of the work. When it helps, I also build the platform or product around it end-to-end, and help your team adopt AI tooling responsibly.
How we can work together
The same senior operator, two contract shapes, chosen to fit your constraints, not the reverse.
Staff augmentation · day rate
I join your team.
I work inside your team, on your stack and your roadmap, at a day rate. You keep direction and priorities; I bring senior data engineering capacity from day one.
Best whenYou have ongoing work, internal context to absorb, and want flexible senior capacity without a hiring cycle.
Fixed scope · I own delivery
I own a deliverable.
We define a clear scope and outcome together; I own delivery end-to-end, from architecture to a system that is live and documented. One price, one accountable owner.
Best whenThe outcome is well-defined (a pipeline, a platform, a migration) and you want a result, not a headcount.
Either way, you end up with the same thing: a system that is live, documented, measured, and yours.
Capabilities
Data engineering is the heart of the practice; the other three extend it, so you go from raw constraint to a running system without handing off between vendors.
AWS-native
I build production-first data systems on AWS: from messy, real-world inputs to pipelines and architecture that are live, observable, and yours to run.
Where this shows up
Data pipelines
Ingestion-to-serving pipelines built for reliability and repeatability.
Cloud infrastructure
AWS architecture as code: secure, observable, cost-aware.
Documentation & retrospection
Mapping and documenting existing systems so they can be understood, trusted, and evolved.
Troubleshooting & debugging
Diagnosing and fixing failing pipelines and brittle data flows under production pressure.
Strategy & business alignment
Connecting the data architecture to the outcomes the business actually needs.
GDPR compliance & security
Privacy and security designed in from the start, end-to-end.
End-to-end
I design, build, and operate full platforms and applications end-to-end: frontend, backend, infrastructure, CI/CD, and monitoring.
Proof: TrainSphere, a two-sided marketplace designed, built and hosted solo, live and monitored.
Problem to shipped
I take a problem to a shipped product: scoping, architecture decisions, and the judgement calls that keep a build simple, useful, and maintainable.
Fewer abstractions, clear ownership, decisions you can explain. Product depth, not just code.
Workshops or régie
I build the workflows and integrations, then train your team to use them responsibly, with governance fit for regulated environments. For example, an intelligent AI reviewer for merge requests, adopted company-wide.
The 5 Pillars
Delivered as a community of practice with governance, proven inside regulated quantitative finance.
AI enablement
Beyond building, I run hands-on sessions that show teams what AI is genuinely good for and how to use it well: the practices, the guardrails, the limits. The same talks I give on LinkedIn and inside companies.
My “Five Pillars” series on Claude Code: hover to preview, tap to open.
Next step
Tell me where the data hurts, and I’ll tell you what it takes to make it run.
Get in touch