Working on a large codebase without any tests can be nerve-wracking. One wrong line of code or an in-conspicuous library update can bring down your whole production pipeline! Data pipelines start simple, so engineers skip tests, but the complexity increases rapidly after a while, and the lack of tests can grind down your feature delivery speed. It can be especially tricky to start testing if you are working on a large legacy codebase with few to no tests. In long-running data pipelines, bad c...
