How to append new numerical features to an embedding from word2vec, such that KNN on embeddings is not biased for one feature?
Since you have mixed data, use one-hot encoding for the categorical data so that they become binary data. For the numerical data, normalize them so that their ranges are within [0,1].  

Next, you'll have to choose an appropriate distance measure. See the answer here:
https://stats.stackexchange.com/questions/218092/how-to-calculate-the-distance-in-knn-for-mixed-data-types