Data scientist here. It really depends on what kind/size of data you intend to work with. If you want to work with enormous data sets, focus on Hadoop and Machine Learning. You won't be able to learn a lot of Hadoop on your own since it really requires having a working cluster and breaking it, but you can get some idea.

For smaller data sets, R will work, and Python acts as glue. In general, on a daily basis, I spend about 70% of my day finding and cleaning data (a lot of data scientists will say the same) and getting it in the shape I need, and only then running algorithms over it.

I work with fairly small-to-medium sized data (now..previously I was at Hadoop scale) and my tools of choice are: SQL for getting the data I need (you will need to become really good at SQL..almost everyone uses it everywhere, really great universal skill to have), Python (pandas) for cleaning the data and making that cleaning process reproducible, then high-level algorithm analysis in R, and presentation either in R or Tableau.