I think if you have the desire and the time to combine these skills, then it's a good idea to do this. If you enjoy building and optimizing pipelines and if you

I think if you have the desire and the time to combine these skills, then it's a good idea to do this. If you enjoy building and optimizing pipelines and if you enjoy doing creating analytics, stats and building models, you will be very much in demand and it will be pretty lucrative. Most people don't do this, because it takes a long time, and they enjoy one over the other. 1. This really depends on the DS role at a company. You are describing a company where DS is highly valued and has a lot of power. They probably have representation with a VP or in the C suite. Some companies are like this. 2. DE should be foundational, and they should also be able to push to production. You might have another team which works on setting up new platform environments, but DE better be comfortable pushing and debugging issues in production. It's helpful for DE to be able to perform exploratory analysis on a dataset. It's easy to introduce bugs, if DE can catch this, then it really improves the velocity. If they can't do this, then you need to wait for DS or somebody to act like QA for a dataset. You can find cheaper DEs who are good at shoveling data around, but they don't know what a probability distribution is. 3. It's helpful for DS to have some domain knowledge. If they have that, and DS is highly valued at the company, then it makes sense for the DS role to contain a Product Management component. I'm glad you are interested in my thoughts on this. If you have any more follow up questions, feel free to ask.