Roles by discipline
Data roles where somebody owns the answer being wrong
Every data engineer has had the Monday morning where a number is wrong in a dashboard someone senior is looking at, and the organisation discovers in real time that nobody owns the answer. Whether that morning is a bad day or your entire job comes down to one thing: whether the pipelines are a product with agreed service levels, or a shared utility everybody depends on and nobody funds. We ask which one it is before we ask about the stack.
What we ask before we post one
The questions the ad never answers.
- When a dashboard is wrong, who is accountable, and what happens next?
- Are there service levels on the pipelines, and what happens when one is missed?
- Batch, streaming or both, and honestly, which of them is in production?
- How many dbt models, and what is test coverage on them today?
- Does the data team report into engineering, or into a business function?
- What is the oldest pipeline still running, and who understands it?
What we will not post
We do not post analyst work with a data engineering title on it.
For hiring teams
Hiring for this discipline?
We work through the role and hiring criteria with your team as part of embedded recruitment. Talk to Jonathan about what you need to hire.