I recently hired into a data analytics team

I work in Data Engineering and have spent most my time on analytics teams. They don't have a SWE/CS background and generally because of that don't follow any good programming practices. In my experience style guides are hard to get them to follow properly even if you set up SQLFluff for them., I can barely make them see the advantage of not committing directly to main (at least we're using git). It's very frustrating.

I think it depends on what you want to put in the header. An overall description of the file, it's goal, etc - that sounds great.

A changelog saying who changed what, when? Our version control system is tracking that for us already.

Hmm, do I want to open some external site/program to see my documentation or have it already in the code in front of me?

We use doxygen at my company and I think I've only ever opened it twice in 9 years.

Yes, serious people write docs. I hate this bullshit about code that should be so good that it's "auto-documenting." It never happens in real life. Code is at best of average quality, but it needs documentation. At my previous job they had "guidelines" to make sure that code didn't needed doc. It was a bad joke and we had the worst code I've ever seen.

I don't have solutions for you though. You need a combo of documentation generation, code formatter (in the CI maybe, or before a commit), and code linters to check for errors.

Commenting your code is an industry standard. Some kind of separate comment metadata won't generally work, unless you code exclusively in spreadsheets, where you can add a note to each cell.

Given that it's a hospital, I guess your management will listen to whomever performs bureaucracy better, not whomever codes better.

A header might be useful, although there's likely better ways to (not) document what each sql statement does.

But inline documentation? I'd suggest trying to work around that. Here's an explanation as to why: https://youtu.be/Bf7vDBBOBUA

If possible, and as much as possible, things should simply make enough sense to be self documenting. With only the high level concepts actually documented. Everything else is at risk to be outdated or worse, confuse

What do you mean by Code headers?

I hope you don't mean those "Created by:" and "Last edited:" things... If yes, please don't!

Your friend may have a point.

It depends where the SQL is.

Is the SQL in a data model in an analytics platform? Some platforms will happily carry comments around like last week's pizza during query generative phases of visualization, so it may not be appropriate to put comments inside a data model, as those comments could become bugs if the analytics platform is lame, like most are.

Others, certain flavors of SQL DDL (Tables, views, etc), comments outside the DDL don't make it inside the resulting object, so headers may not be the right place either. Most RDBMS have meta-descriptors that can apply to DDL so those might be good to look at.

For arbitrary SQL, outside a brief inline comment describing why it exists, and what invokes it, your next best bet may be a link to a more descriptive data architecture diagram that shows how this unit of SQL integrates with others. You might prefer hyperlinked descriptions from that data architecture over searching thru code.

As long as comments don't require continual parsing (a one-time tax is inconsequential), definitely add details that you have figured out so others don't have to re-learn the tribal mysteries of long-deceased ancients.