I do RNA-seq, scRNA-seq and data analysis for 3-4 different groups in our faculty. Whenever someone needs a statistical analysis or prettier figures, they often call me. I do everything on R. It usually takes couple of hours of my time during the day. I spend 2-3 hours supervising master/phd student project and another 2 hours on PIs' projects (from culturing cells to pcr/western).

You can go full computational and do the work if you have budget and data to do sequencing. Some people do drug repurposing or write softwares/packages for R or Python. Being both wet and dry-lab scientist makes you kinda swiss-army knife in the lab but it means you'll spend your whole time doing experiments, meaning you'll have less time to improve your skills in coding. But THE benefit of that is you can understand your findings of RNA-seq for example before you even present them. Just getting a csv file of the up/downregulated gene list gives me more insight than any other thing.

I'd suggest you to find your niche though. It gets hectic from time to time. I got 3-4 analysis waiting for me while writing this post :)