Data Linter

About Data Linter

Python package for automated data validation within Data Engineering pipelines. Engineered to ingest and validate tabular data against predefined schemas.

Key Features

• 1Validates tabular datasets against a set of configurable lint rules
• 2Checks for PII columns, low-cardinality strings stored as plain text, and more
• 3Configuration-file-driven rule sets for team-wide standards enforcement
• 4Outputs structured JSON results for integration with CI systems
• 5Designed for use in data pipeline CI/CD checks

How Python Data Engineers Use Data Linter

Data engineers use Data Linter in CI pipelines to enforce dataset standards before promotion to production. Running `data-linter` on a new dataset file flags issues like potential PII in column names or inefficient data types — catching structural problems early in the development workflow rather than after data lands in the warehouse.