How important is engineering for a data scientist?

A common thing I notice among Data Scientists is that their code is generally questionable, very unoptimised, and always in a Jupyter notebook.

Anything related to deployment or general algorithms are typically ignored

I can understand that in larger companies there are other teams that can take a model or the analysis and handle the engineering, but surely there should be a base knowledge and understanding expected from someone with the title “Data Scientist”?

What are your thoughts? Can a …

algorithms analysis code companies data datascience data scientist data scientists deployment engineering general jupyter notebook scientists teams