When is feature transformation required?

Question

I was fitting machine learning models to clean data(Imputed missing values, removed unnecessary features etc). I didn't transform the features that are skewed. Before moving forward, I want to understand how important feature transformation is to fit data into a model. Any opinions?

(I know what happens in Random Forest, but unable to comprehend for other ML models)