Catch the 90% of stuff that works with your cut down dataset. The other 10% includes things you might only catch not only with O(n^2) queries over a 10TB, but also when under prod load like you say.
Just either gradually roll out those high-risk changes with feature flags, etc. or make sure your monitoring is up-to-scratch so you can catch issues and fix them.
Totally seconding the 80/20 rule here. It's probably less frustrating and faster for everyone if you can work on compartmentalizing failures that do slip through or only happen for those two customers with very special data sets that you most probably wouldn't catch in testing either because your test suite won't execise the full 10TB data set anyway (assuming here because we don't know your product)
Just either gradually roll out those high-risk changes with feature flags, etc. or make sure your monitoring is up-to-scratch so you can catch issues and fix them.