Depends on the setting. I have built python ETL pipelines for some of my customers, it’s slow, not efficient but, every data scientist can read the code and mak

Depends on the setting. I have built python ETL pipelines for some of my customers, it’s slow, not efficient but, every data scientist can read the code and make it work for their changing requirements. At the end of the day, if you’re running a 3hour etl job in Python or 1h on a Spark/hive/mapReduce/what else legacy tooling they got I’d choose 3H one if team can support it and is not afraid to make changes.