About
Where systems meet
Most of my work happens where systems meet: a screen and the service behind it, a calculation and the SQL that feeds it, an application and the identity, secrets and pipelines it depends on.
About & collaboration
I'm comfortable starting in an unfamiliar codebase. I read the business logic, map the moving parts, and write down what I find, whether that's a functional and technical write-up of a calculation process or a UML-style diagram of an API's object model.
I started out in NLP and machine learning at university, and I'm now steering my career back toward AI and data engineering. I bring habits from enterprise work with me: validate everything, reconcile the parts to the whole, and document how the numbers are derived.
How I work with teams
- Explaining the work. Translating technical findings for business and engineering stakeholders, including demos to senior engineering and architecture leads.
- Unblocking others. Helping developers with deployment setup, branch merging and GitHub workflows.
- Handing over well. Knowledge transfer and written documentation, so fixes outlive the ticket.
- Working across teams. Coordinating with platform and support teams on access, identity and environment changes.
The path so far
From university projects in NLP and ML, through enterprise engineering, and on toward AI and data engineering.
Get in touch
Happy to talk about data engineering, data correctness, AI-assisted development, or roles in AI and data.