You can use python libraries in Spark. I suggest using fuzzy-wuzzy for computing the similarities.

Then you just need to join the client list with the internal dataset. If you wanted to make sure you tried every single client list against the internal dataset, then you can do a cartesian join. But there may be a better way to cut down the possibilities so you can use a more efficient join - such as assuming the internal dataset name starts with the same letter as the client list. You can even try multiple passes on the internal dataset and try more complicated logic each time.