The biggest misconception that people have when modeling using tabular data is that more data = better model.

You don't need to. Just sample 1% of data, let the model do the feature engineering, ask model model to replicate everything in Pandas (or R, or whatever else), so you can run it for a full dataset.

Big Data is terrifying and only solvable with opaque deep learning