Welcome, @ynanyam
The short answer is that the environment that the tool is running in cannot “see” sqlalchemy (even if the server environment can). This can be rooted in a python versus problem, or a “lost environment” due to other reasons.
A Galaxy server can have multiple modes or destinations for running jobs. Some might happen locally and some might be dispatched to a cluster in a container environment, or to just another server or cluster. Maybe one has a problem, and the others don’t.
If you want to check that to see if it helps where to look first, then let us know if you need more help, it might be a good place to start. The version of Galaxy you are running and some details about your job configuration would probably help us to help you, too. Are you using dependency resolvers? Are you using containerized job environments?
Meanwhile, I’ll post some of our resources that add in more context about how distributed job running runs plus help about containers.
Maybe start with these?
- Galaxy Job Configuration — Galaxy Project 24.1.0.dev0 documentation
- Containers in Galaxy — Galaxy Project 24.1.0.dev0 documentation
- Galaxy Server administration / Tutorial List → see Jobs & Scheduling
With all top levels of those guides starting from here.
I’m going to cross-post your question over to our Admin chat to get some feedback, too, since this is about as far as I can take you! Maybe someone recognizes the problem and can offer a quicker fix suggestion! They will probably reply here but feel free to join the chat! 
→ You're invited to talk on Matrix
Let’s start there, thanks! 