Most of my work outside of the day job is developed on x86 and deployed on ARM.
Unless you're talking about native code (and even then, I've written in the past about ways this can be managed more easily), then no, it really doesn't matter.
If you're developing in NodeJS, Ruby, .NET, Python, Java or virtually any other interpreted or JIT-ed language, you were never building for an architecture, you were building for a runtime, and the architecture is as irrelevant to you as it ever was.
Well I can't speak to some of the others... but Conda doesn't work at all on ARM today (maybe that will change with the new ARM Macs, though), which is annoying if you want to use it on, say, a Raspberry Pi for hobby projects.
Additionally, many scientific Python packages use either pre-compiled binaries or compile them at install-time, for performance. They're just Python bindings for some C or Fortran code. Depending on what you're doing, that may make it tricky to find a bug that only triggers in production.
Unless you're talking about native code (and even then, I've written in the past about ways this can be managed more easily), then no, it really doesn't matter.
If you're developing in NodeJS, Ruby, .NET, Python, Java or virtually any other interpreted or JIT-ed language, you were never building for an architecture, you were building for a runtime, and the architecture is as irrelevant to you as it ever was.