I'm not in the business as long as you are Steve - roughly 1/3rd of your time - and I only very recently started to care about data outside Performance and DR but from supporting Developers previously, I think some of the challenges remain the same, back then, today and potentially tomorrow.

That would be first and foremost data management. Remember all those functions, procedures, expressions we've had to form back then to get Excel exported dates back to something useful? We still do and we potentially still will be doing in the future. Another problem I would call is data sourcing: Do I really need 20 exported CSV Files to get all the data I want to process or have requirements changed that much so I could potentially just get 2 or 3 large CSV Files with all necessary data? After all we are processing more data today than 10 years ago. 

And with processing more data I think we will see more transformations towards different approaches of data and data processing. Is the data a snapshot? -> Most likely your plain old ETL Process for the next decades to come. Is the data a continuous stream? -> As we certainly want to remember the interesting things from our data streams, we'll keep those but we still want to process the stream continuosly, for things like that we will see much more use of things like Hadoop and Machine Learning so yeah, we will and do see a lot of new challenges waiting for us. Might be a little bit different as we might not be looking that much at index optimizations anymore but rather wether our ML algorithms do enable our business to make the decisions reliably to our advantage or not?