Worked on the OpenSTEF/openstef repository to enhance wind feature engineering by implementing a new condition that extrapolates wind speed to 100 meters when windspeed_100m data is missing. This solution addressed data gaps by applying conditional logic in Python and Pandas, ensuring that downstream wind analyses remain reliable even with incomplete input. The approach included updating unit tests to validate the handling of missing wind speed data, supporting test-driven development practices. By focusing on robust data engineering and feature engineering, the work improved the maintainability and accuracy of wind-related features, enabling more dependable modeling and analysis within the project.