I still remember the good ole days when Apache Spark was fresh and hot, hardly anyone was using it, except a few poor AWS Glue and EMR users … Lord have mercy on their ragged souls. It’s funny how that GOAT of a tool went from being used by a few companies for extremely large datasets … to today’s world, with Databricks, where Pandas-sized data is crunched with Spark.
Recently, for some unknown reason, I was pursuing the new Stackoverflow … called Reddit, for Data Engineering … and I ran across an interesting question … more or less it was related to “what makes a good Software Engineer … in a Data Engineering context.”
One thing I find myself doing these days (I am unsure how I feel about this), is teaching others to solve problems … Data Engineering problems to be specific. It’s not a hard stretch for most to imagine that what a person does at Senior+ software-type levels is just write good code all day.
I assure you, this is not the case typically.
