Personally, I hated databricks, it caused endless pain. Our org has less than 10TB of data and so it's overkill. Good ol' Postgres or SQL Server does just fine on tables of a few hundred GB, and bigquery chomps up 1TB+ without breaking a sweat.
Everything in databricks - everything - is clunky and slow. Booting up clusters can take 15 minutes whereas something like bigquery is essentially on-demand and instant. Data ETL'd into databricks usually differs slightly from its original source in subtle but annoying ways. Your IDE (which looks like jupyter notebook, but is not) absolutely suck (limited/unfamiliar keyboard shortcuts, flakey, can only be edited in browser), and you're out of luck if you want to use your favorite IDE, vim etc.
Almost every databricks feature makes huge concessions on the functionality you'd get if you just used that feature outside of databricks. For example databricks has it's own git-like functionality (which is the 5% of git that gets most used, but no way to do the less common git operations).
My personal take is databricks is fine for users who'd otherwise use their laptop's computer/memory - this gets them an environment where they can access much more, at about 10x the cost of what you'd pay for the underlying infra if you just set it up yourself. Ironically, all the databricks-specific cruft (config files, click ops) that's required to get going will probably be difficult for that kind of user anyway, so it negates its value.
For more advanced users (i.e. those that know how to start an ec2 or anything more advanced), databricks will slow you down and be endlessly frustrating. It will basically 2-10x the time it takes to do anything, and sap the joy out of it. I almost quit my job of 12 years because the org moved to databricks. I got permission to use better, faster, cheaper, less clunky, open-source tooling, so I stayed.