How to structure my data into features and targets for PCA on Big Data?
First of all, if the "weight" etc. attributes should not be used for clustering, then don't include them. It makes you question hard to follow. On the other hand, if you don't include them  there is obviously no difference between the kids... So I'm not certain you have understood what you want, need to do, or ask for.

PCA is not a magic tool that makes you data clusterable! It is a very specific tool to decorrelate data that should only be used when you have strong, known, linear correlations in your data that you need to ignore. It will not work when you have non-linear correlations (e.g., income and number of yachts), or when your data is not continuous on a linear scale. In particular you shouldn't use it on your first attributes such as date, state, etc.

What you first will want to do - and that has nothing to do with PCA nor clustering, is to pivot your data to separte the kids. Consider transforming your messy table into "tidy data" form first, this will make such cleanup much more structured and easier to do.