I just enjoy working with raw data and raw code more than I enjoy writing something that launches a graphic. I enjoy writing a script that finds a bad piece of data, or a script that fixes up everything, or writing something that was once unable to run at all get converted to something that runs in 500ms. Perhaps it is that journey of constant discovery, and seeing that every situation is a unique little puzzle. It is seeing the world as it is with no one reinterpreting what the data means for me. I can explore it and discover what it really means. It is hollow truth, a mess of ideas converted to sets of ideas layered on sets of ideas, and when it is finally drawn down, converted, and passing all tests, it is self-evident and self-reflecting, and true. Hard to explain, but I suppose I like all the things people hate about it.
The tools matter about as much as it matters what CSS framework you are using. You have the ability to logic through UI and UX, whereas I do not. I have zero hope of ever doing well at what you do, since I simply don't have the foundation, but if it matters, I know most jobs I've applied to and worked at tend to be more ad hoc, using PL, Python, Ruby, etc.
I know this isn't reddit, so I'll point you to reddit. Check out /r/datascience where those folks talk about what it takes to be a data scientist. Some folks are honest about data engineering, but most handwave past it, or talk about it like it's beneath them. Their role would not be possible without solid data engineering, rather than a complementary and equally important discipline. Good luck doing "data science" or "analytics" or "machine learning" or every other buzzword without clean data, and for us data engineers, good luck ever demonstrating value without the analytics folks working with us.
Don't sell yourself short or select yourself out of an opportunity (within reason). That's someone else's job!
