The issues I encountered working as a data engineer many moons ago, is that in a business that's either agnostic to data quality or doesn't invest in reliability, the data engineers tend to become the face of failure. If a Kafka queue begins acting up, or a data ingestion jobs fails because of some upstream data source changes, then it's usually up to the data engineer to...
1. Notice that something's gone wrong.
2. Figure out who in the organization is going to be affected and let them know.
3. Run any triage and comms with the business keeping them in the loop until it's fixed.
In my experience, like the guy who only gives good news to the dictator, certain execs/leadership would quite happily let data engineers take the lead for outages, only swooping back in once everything was up and running again to demand a report on "how this happened" and some glib advice to "take time to stop this happening again".
While it can be technically rewarding as a career move, it's got to be highlighted that it's only fun and games until you hit your first major outage.