So your options are either senior software engineers who have done some data work (that's how I got to be a Data Engineer) or people who've been doing analytical data work (either in the traditional warehousing space or via science/insurance/finance type spaces) that are semi-technical but have no formal engineering background.
The former are people who went to college in the late 90s/early 2000s (like myself) when things were different. The latter need to hyperfocus on coming up to speed in engineering.
I reviewed this guide a couple months ago for my employer to consider as the basis of an internal bootcamp, and I'd note that it's perfect for the audiences I mentioned. Also, even for people with more up to date academic experience, note that the transactional database schemas that software normally deals with often look wildly different than analytical structures.
I have kept up to date on these technologies, I participated in undergrad research on distributed systems and my career has revolved around them. Many devs never really get a say in where their data goes, they might read a blog post or two about new systems, but it leaves a very light imprint. Its been rather spotty as to whether I had any say in where my data is stored throughout my career.