I've seen some "data engineering" scripts that were complete messes and beyond crazy. Some examples: Massively over engineered "pipelines" that process a few hundred rows a day, but somehow manage to take forever to run. Developers that didn't know SQL beyond "select * from table", so they do all their summarization in Python. Or, worse, I've seen a Python script calling a shell script calling R calling something else, several more layers deep, when the same result could've all been done in SQL with a few temporary tables.
Oh, then I'm asked to "give this a code review before so-and-so does a deployment tomorrow." Uh, it's a little late to address any of the fundamentals, but there are hard coded paths everywhere...
Oh, then I'm asked to "give this a code review before so-and-so does a deployment tomorrow." Uh, it's a little late to address any of the fundamentals, but there are hard coded paths everywhere...