That's interesting, because I usually hear of people having the exact opposite experience. The appeal of SQLAlchemy is that it lets you work at any level arbitrarily—you can use its high-level operations and abstractions for the 80-90% of common cases, but then drop down to its lower level and write complex queries where needed (including CTEs, window functions, stored procedures, etc), without ever resorting to writing SQL by hand. Django's ORM, in comparison, is very limited in the types of queries you can write with it, and is difficult and unintuitive to optimize.
Edit: That said, the Django ORM has improved by leaps and bounds over the past few years. These days, I'd say it gives you a way to cover about 90% of cases in an efficient manner (even if it has a bit of a learning curve). But if you're consistently doing more complex queries, I think SQLAlchemy is vastly superior.
I think a good ORM is one that strives to make 80-90% of operations ridiculously easy, leaving edge cases to the developer who can always drop down to a raw query as needed. Django does that fairly well, IMHO, and my limited experience with SQLAlchemy felt pretty underwhelming in comparison
EDIT: Though admittedly I did not have access at the RDBMS level to write VIEWs to match my business needs back when I was using Django. If I did, then perhaps I could have chosen that approach – though I would have to forgo all the useful django-admin stuff that comes out of the box, so there's always a tradeoff...