It really helped in our case. We have a team of 10+ researchers who alse ship code in production. They were repeatedly running into a problem where they recompute same data in runtime, or reinvent the wheel because they didn’t know somebody already computed that datum. I end up writing a small single-process (for now) workflow engine running a “company-wide DAG” of reusable data processing nodes (all derived from user-submitted input + models). Now it is much easier for individuals to contribute + much easier to optimize pipelines separately. I might open source it some time soon.

It's what is done de facto by large enough groups anyway. They just have to kludge tooling together for it.