What is a data contract for ML features?
PICTURE THIS: DATA SPLIT
Fit on train, tune on val, report on test once.
Simple meaning
A contract is a schema plus semantics: types, null rates, allowed ranges, and owners.
WHY — Feature Pipelines instead of guessing?
Why interviewers care about Feature Pipelines:
people who only read docs from people who shipped.
and tied to MLOps work.
Name the idea, why it exists, then one short example.
End with when you use it and one common pitfall.
STEPS — What happens step by step?
Before you speak the answer, walk the interviewer through these steps:
- 1A contract is a
schema plus semantics: types, null rates, allowed ranges, and owners.
- 2Producers cannot silently rename
a column that models depend on.
- 3Tools like Great Expectations
or warehouse constraints enforce it in CI and in production.
- 4Give an example
One tiny concrete case you can say aloud.
- 5Common mistake
What juniors usually get wrong.
- 6Close
When you pick this over the alternative.
EXAMPLE — See it in action
Here's a short line you can speak, broken into clear beats:
Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.
Key takeaway
A contract is a schema plus semantics: types, null rates, allowed ranges, and owners. Producers cannot silently rename a column that models depend on.