[D] Feature engineering in deep learning when the data is limited

I have read that feature engineering for deep learning can limit how much the neural network is able to learn which makes sense if there's a lot of data.

But what if the data is limited? Wouldn't feature engineering help in such cases so that the network doesn't have to rely on tons of data to learn what features are useful from what is noise?

cases data deep learning engineering feature feature engineering learn machinelearning network neural network sense