According to this recent post from JP Kabler, you're not a data scientist just because you work with Hadoop a bit, and know some Python, and have some chops when it comes to databases. Kabler says:
You can write map-reduce jobs in Hadoop, you know Pandas well enough to aggregate and merge and transform and join on the fly. You're a data scientist!!
Except that you're not. I'm not either.
Kabler's point, ultimately, is that there is a lot more to being a data scientist than most people think, and he provides a number of interesting resources to help aspiring data scientists make sure they're on the right path. The most interesting is definitely Swami Chandrasekaran's subway map-style visualization of the knowledge needed by data scientists, but Kabler also points to a guideline to data science proficiency that he is currently following.
It's hard to tell how effective such a road map might be - maybe Kabler will update with his progress - but either way, it's an interesting viewpoint and potentially a good way to learn more.