A data contract is an explicit, versioned agreement between the team that produces a dataset and the teams that consume it, setting out its schema, its meaning, its update frequency and its quality rules.
The contract describes the fields, their types, the allowed values, the expected delivery time and the procedure for breaking changes. It is written in a machine-readable format (often YAML) and checked automatically: a change that breaks the contract is blocked before it reaches consumers.
The problem it solves is common: an application team renames a column, and the dashboards or machine learning models that depended on it break silently.
It is found in mature data organizations, often alongside a data mesh approach. It relies on standards such as the Open Data Contract Standard, data quality testing tools (Soda, Great Expectations) or a schema registry for Kafka streams.
Why it matters when hiring
It is a topic for a senior Data Engineer or data lead, as much organizational as technical. The good signal: a candidate who got a product team to adopt a contract, not just wrote a YAML file. Ask how they handled the first breaking change. Requiring this skill in a small data team without multiple producers is often premature.