Oh, and it's real plumbing...
Now that is a standout line right there. It perfectly describes some of my own personal projects. Sometimes—oftentimes—they go nowhere but I had fun.
One such task was developing a secret Santa system in python with an auto mailer and “paper” backup while in Hawaii last year. It took me part of a morning during breakfast before we went out for the day. I refined it when we got home. There were others already out there and it did nothing more then putting names in a hat, but it was fun. And it’s reusable. And it had the added benefit of needing no moderator—nobody in on the secret.
The metaphor of a wood working project just seems to fit so well. Nice one.
Hate your job? Maybe it's the job, not the profession. Developers have an enviable amount of mobility; use it.
Maybe you aren't taking care of yourself in some other way? Sleep, diet, exercise, possible clinical depression: these are all things to try.
Perhaps you're burned out? It's 2020, that's a very real possibility. There's a whole literature on what to do about it, and "abandon your career" is dead last.
Both of the preceding paragraphs have a "talk to your boss" component. Don't think that's a good idea? Great, you definitely have the wrong boss, GOTO LABEL "Hate your job?".
Good reasons to stop developing software: a) there's something else you really want to do, and you have rational confidence you won't starve, and b) you're ready and able to retire.
Bad reasons to stop developing software: literally anything else.
If you're currently on that trajectory (i.e. you're able to save a large percentage of your income every year) then I'd recommend it. If not, then yeah, you might need a second career if you want to get out of development soon. My plan is not to need one.
You get to talk worth a bunch of people in sales and still exercise your problem solving skills.
Meeting users, finding out about their problems and working out how software can solve them?
In the agile world, the analysts were basically replaced by product owners, but I assume there are still places where they exist. I've done it for a while, it's quite cushy job if you're good at talking, writing, presenting (same as product owner but without the "ownership" part, so much less stress).
So essentially we became figureheads. Our work rarely was used in any significant way or provided much value, but we were kept around because the company wanted to be able to tout its “data driven” culture.
It was so bad that at one company I worked for, they had the data science/analytics department start putting on a yearly intracompany conference on analytics that became a huge deal. One year they got Stephen Levy, the author of Freakonomics, to be the keynote speaker. At one point he shared a story about how he was consulting with a company on their marketing, and they found that they had accidentally not been running ads in a particular metro area, and were able to leverage this to act as a control to assess the materials effectiveness. But when asked to intentionally do something similar moving forward, the company balked. It was so close to home that my colleagues and I wondered if the head of our department had fed him the need to talk about it. And yet, not a single thing changed at the company during my time there.
I currently work in a role much closer to software engineering, and I have all of the same problems described by the person in the original post and that many are describing here. But I consider it a strict upgrade over my time working as a statistician.
The situation in research is exactly as you describe -- we are figureheads who are put into place and highly pressured to confirm whatever hypothesis a PI wants for their latest grant or paper. They would never ask us to commit fraud, only perhaps to "double check" an analysis 10 times until it shows what they want to see.
If I were working for a company, this would at least be understandable, as companies don't even have a theoretical commitment to truth and scientific integrity, and there are no real consequences to a faulty analysis.
But it is immensely galling to see in research. Here we are, paid by the public to supposedly pursue truth and improve human health, and instead the job is to constantly be finding ways to avoid fraud and fabrication without pissing off the collaborator. The result is, as you say, useless analyses if the analyst is honest, and fabrications if they are not.
There is absolutely no doubt in my mind that this is one of the key reasons the ROI on science has declined drastically in the last few decades. It makes me laugh bitterly every time I see (increasingly frequently) political exhortations for plebeians to "trust the science".