Developed four Rust-based string distance and similarity user-defined functions for the Daft repository, enabling advanced fuzzy matching and data cleaning in analytics pipelines. The implementation included Levenshtein, Jaro, Jaro-Winkler, and Damerau-Levenshtein algorithms, all exposed through a Python API and designed for null-safety to prevent downstream errors. The approach followed established patterns to minimize dependencies, using pure Rust and aligning with existing code for maintainability. Comprehensive validation was achieved with 24 Pytest cases, ensuring correctness and robust null handling. This work enhanced data quality in ETL workflows and supported downstream machine learning features by improving deduplication and matching capabilities.