Pros
- good data engineers to learn some things from, good team of data scientists, and an overall good engineering department
Cons
- The data management was pretty much nonexistent, the person on the job didn't share a vision with concrete projects for the team, he was looking into a way to come up with some shady ML project that didn't use ML at all - CEO has no idea of the current state of the platform he's trying to sell - The data team had good folks, but an alarming rotation level, indicative of poor management - Lack of communication between engineering departments, I had one meeting gathering the engineering teams to learn about the projects other teams were working on in 4 months. - Constant shifts of the organizational structure lead to more confusion and less focus on the work needed