Works with
Hire one when
- Nobody trusts the numbers in your reports
- You are preparing data for an AI project
- Exports and syncs break and are fixed by hand
What they do
What a Data Engineer does for you.
Build and monitor data pipelines
Design databases for the queries you run
Clean and join data from different systems
Prepare documents and records for AI search
Write down definitions so numbers mean the same to everyone
Engineers from our own team, matched to your stack.
Start with a callHow hiring works
Four steps, no CV pile.
- 1
Intro call
What you're building, the stack and the seniority you need.
- 2
Matched engineers
We put forward engineers from our own team who fit, not a stack of CVs.
- 3
Trial week
They work on your real backlog, so you judge the work, not the interview.
- 4
Embedded
Your stand-ups, your tools, your code review. Scale up or down as you need.
Often, yes. Clean, permissioned data is the biggest factor in whether an AI project works.
Yes, usually in Metabase or your existing reporting tool.
Typically within one to two weeks of scoping the role, because our engineers are already part of our delivery process.
Engineers from our own team. We do not resell freelancers from a marketplace.
Either works: you manage the work directly while we handle technical oversight, or we manage the engagement end to end.
Other roles
Build the rest of the team.
AI Agent Engineer
Agents and tool-using workflows, built for production.
LLM Engineer
LLM applications across OpenAI, Claude and open models.
Claude Developer
Products and agents built on Anthropic's Claude.
RAG Engineer
Search and retrieval over your documents and data.
Full-Stack Engineer
React, Next.js and Node, from database to interface.
Mobile Engineer
Flutter apps for iOS and Android from one codebase.