All the Spark GPU acceleration right now is done via the Spark-RAPIDS plugin, so HIP would somehow have to support that. Since cuDF is the core part and hipDF is a thing, it might be doable in the near future.
This is one area where it is clear that Nvidia is a leader by not only providing the underlying kernels, but also the overall product framework integrations. One would have to port that entire plugin project over, which would probably be a ton of work to maintain.
For what it is worth, AMD just recently released two blog posts on hipDF, so at least they are putting that effort in.
https://rocm.blogs.amd.com/artificial-intelligence/cupy_hipd...
https://rocm.blogs.amd.com/artificial-intelligence/hipDF_pan...
As you learned at the event, Modular is trying to make it more transparent by abstracting to a whole new language (Mojo).
Another solution coming down the line which doesn't require changes to your CUDA code, nor learning a new language is: https://docs.scale-lang.com/
If I had to bet on the longer term, I think that something like Mojo will win out -- a programming language (mostly) agnostic to the underlying vector processor hardware. Similar to how Rust can target various SIMD implementations, though I've only dabbled in that.