project · 2023-2024
Schema-aware data validator
Built a Python validation library that turns sample events into editable contracts with reusable field-level quality rules.
The problem
Adding quality checks to a new event type often meant writing bespoke validation code, creating uneven coverage and avoidable maintenance work.
Approach
- Generated an editable schema from representative event data.
- Supported reusable null, range, allowed-value, and custom validation rules.
- Packaged the library for consistent use in data-ingestion workflows.
Outcome
Engineers could define clear event contracts quickly while keeping validation behaviour consistent across pipelines.