How they handle a late-arriving record
Exposes whether they have run pipelines against real-world data.
Data engineers who deliver datasets people trust — which is a different job from delivering pipelines that run.
Written as the work, not as a keyword list. If your role needs something outside this, tell us and we will say whether we can staff it.
This is useful whether or not you hire through us. A better-run interview gets you a better engineer either way.
Exposes whether they have run pipelines against real-world data.
The debugging path reveals how well they understand their own system.
Frequently ignored until the invoice arrives.
A pipeline that runs is not a dataset that can be trusted. Ask how they would know if it silently produced wrong numbers for a week.
We assess data engineers on pipeline design with realistic messiness — duplicates, schema drift, backfills — rather than a clean textbook scenario.
Hexalabs is early. We would rather say that than imply a history we do not have — you would find out anyway, and it would cost us the engagement. Instead, here is what we commit to in writing so trying us costs you very little.
Start with a two-week paid pilot on real work from your backlog. At the end you decide whether to continue, with no further obligation and no notice period to serve. You will have seen the code, the communication and the pace before committing to anything longer.
If an engineer is not working out in the first 30 days, we replace them at our cost, including the handover. You do not pay twice for the same seat, and you do not run the hiring process again.
Engagements run on two weeks notice. If it is not working, you are not trapped in it. We would rather you left early than stayed unhappy and told people about it.
You interview every engineer before they join, and nobody is placed without your yes. Our screening notes come with each profile so you can see what we assessed and judge it yourself.
These terms go into your contract, not just onto this page. Ask us for them in writing before you commit to anything.
Two fields to start. The more you tell us about the work, the closer the first set of profiles will be.
Still deciding? A short conversation is usually faster than another round of research.
Ask us directlyWe assess data engineers on pipeline design with realistic messiness — duplicates, schema drift, backfills — rather than a clean textbook scenario.
A pipeline that runs is not a dataset that can be trusted. Ask how they would know if it silently produced wrong numbers for a week.
Either. A single engineer joins your existing team under staff augmentation, working your process and your sprint. If you need the surrounding roles too — design, QA, DevOps — a dedicated team is usually the better shape, and we will say so rather than selling you more people than the work needs.
An overlap window with your working day is agreed before anyone starts, and it is written into the engagement rather than left to goodwill. Tell us the hours you need covered and we will tell you honestly whether we can staff them.
IP assignment is set out in the contract before work begins. Confirm the specific terms with us in writing — this is exactly the kind of thing that should never be assumed.
Python engineers for backend services, data work and the increasing overlap between the two.
ExploreEngineers who can get a model into production and tell you honestly how well it is working once it is there.
ExploreInfrastructure engineers who make delivery repeatable and recoverable — and who have been on call for the systems they set up.
ExploreProduct, design, engineering, QA and DevOps — assembled for you.
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