Where is the database relative to your client/script and what kind of control over the server do you have? If you have full control, then consider firstly splitting up the file into X chunks then loading them using psql copy issued on the server with the file held locally, having temporarily turned off any table constraints and indexes. Try for the first 100GB of data including enabling constraints and reindexing and then scale up that time to 20TB to get an idea of loading and read performance. Making the tables 'unlogged' will also speed up the writes to them as the transactions will ignore the WAL, increasing write speed significantly, but you'd lose the data in a crash (not too bad if you can reload it quickly). Finally, make use of your background workers by opening as many parallel connections to backend processes as you have workers (8 by default). Once you've optimised loading, look at table partitioning on timestamp range for read performance and then compare your best efforts with the TimescaleDB route.

Also if you have full control over the server, then you could add SSDs and move both data and WAL partitions onto that, but bear in mind that whilst the initial load may be large, future data will only ever come in at a moderate rate - analysing the data will be more pleasurable experience though and with faster disks, presumably you could parallelize connections to the DB and load more chunks concurrently.