'Full stack' data science

I'm noticing more and more roles require end-to-end production skills.

Previously a DS role seemed to involve training a model to solve a problem, or creating a POC, then passing it to engineers to put into production. Now jobs want you to own the whole life cycle from training, to deployment, to monitoring, with knowledge of scalability, compute and engineering best practices.

The problem is outside of start ups or small companies where the role has a large scope, it is difficult to develop these skills. Is this similar to others experience and what do they recommended?