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.

Category
AI & Cloud
Roles
4
Screening
By an engineer, with written evidence
Terms
Quoted per role, in writing

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