You need to understand why you want to use resnet architecture. The key reason for using resnet is that as NNs get deeper the inputs to each successive layers become smaller and smaller. This can be circumvented by adding the input data to the output of some layers later.

So in the case of tabular data you need to see why you want a NN and if it is the only thing that works for you. Next question is whether you want to have a very deep NN necessarily. What if you transformed the inputs? If yes, then you should be able to build a skip connections trivially.

Resnet is just the architecture. It has nothing to do with pertaining data. You can have skip connections with linear layers as well.