Hire developers · AI & Cloud
AI & Cloud
Hire Data engineers
Pipelines, warehouses and the modelling underneath them — the foundation that analytics and every AI feature actually depend on.
What they are hired to build
The work, before the CV.
A role written against the work gets a better shortlist than a role written against a stack. These are what Data engineer engineers are usually brought in to do.
Roles we recruit: Data engineer · Senior data engineer · Analytics engineer · Data platform engineer.
- Warehouse and lakehouse builds
- ETL and ELT pipelines with real reliability requirements
- Data modelling for analytics and reporting
- The data layer beneath an AI or ML feature
The technical screen
What the conversation actually covers.
Every candidate has a real technical conversation with an engineer who has done the job, and you get written evidence per competency. In Data engineer, that conversation covers the following.
Usually assessed alongside: SQL, Python, dbt, Airflow, Spark.
- SQL at depth — window functions, plans, and why a query is slow
- Pipeline failure: idempotency, retries and late-arriving data
- Modelling choices and what they would do differently now
- Orchestration, testing and how they know a pipeline is correct
Three ways to bring one on
The route changes; the screening does not.
The same three routes apply whichever stack you are hiring for. Which one fits depends on how long you need the person and whether the headcount is approved.
Permanent placement
Companies hiring engineering and data roles
One fee on joining, with a 90-day replacement guarantee.
- Typical timeline
- 3–8 weeks to offer
Contract staffing & staff augmentation
Companies with budget but no headcount
We employ them, you direct them. Monthly, for when the need is real but headcount is not approved.
- Typical timeline
- Monthly, 3-month minimum
Contract to hire
Companies hiring into a new or unclear role
Three to six months as a contractor, then convert. The honest option when neither side is sure.
- Typical timeline
- 3–6 months to conversion
Or have us build it instead
If the need is the work, not the headcount.
AI & Data
Data platform engineering
Warehouse, pipelines and data quality — the foundation most AI projects discover they are missing.
AI & Data
AI readiness assessment
What is worth automating, what it costs at real volume, and the two things that will block you.
Support & Managed Services
Database administration
Tuning, backups and upgrades for teams without a DBA.