2023 In 12 Data Engineering Errors That Ultimately Advanced My Skills

What new data engineers can learn from my struggles and discoveries troubleshooting Python, SQL and Airflow errors.

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When it comes to errors I encounter while coding or building pipelines, I like to borrow a strategy from Captain Jack Sparrow; just like the pirate code, errors aren’t absolute–”They’re more like guidelines, really.”

Even at the close of a particularly good professional year that involved me working on larger-scale organization projects, collaborating while living abroad and ended with advancement into a senior role, I still cringe when I think of particular errors.

Last year, in a departure from the typical “year in review” type piece, I reflected on errors, both obscure and common, benign and detrimental, and tried to use the opportunity to make fellow engineers aware of their existence. I also sought to demonstrate that, by overcoming these errors, I’ve sharpened my own technical skills.

Here now, in no particular order, are 12 of the most memorable errors I encountered and overcame in 2023 and a warning to those that may be on a path to make the same mistake in 2024 and beyond.