Teams I have coached have taken a few different approaches. Some have treated the data platform as a product. So they create a Data Platform Owner role who engages with the different Analytics teams early to see whats on their roadmap and then works to prioritise what data platform features need to be delivered so the Analytics team can use it. The Platform/Engineering teams treat the Analytics Teams as their customers. Another approach is to collocate a platform/engineer skilled person in each Analytics squad. They build out initial platform features as they are reqiured. Those features are then iterated on in the future as they are reqiured by other Analytics Squads. I have seen wokred with teams where the iteration was done by a dedicated platform squad, but also where it was iterated by the next Analytics squad that needed that feature. Let me knwo if you want any more details on any of these approaches.
Highly recommend Avo (Avo.app). The platform was built with a git-branch type workflow to remove the bottlenecks that stem from less technical teams (product, marketing, etc.) relying on analytics teams to design and communicate what's needed from engineering to measure certain KPIs/metrics. These requirements are usually crafted in a spreadsheet, doc, github, etc. and very few teams know how to contribute, so the dependence on analysts gets them stuck in the middle -- and their time is much better spent elsewhere.