97 Things Every Data Engineer Should Know: Collective Wisdom from the Experts. Edited by Tobias Macey, host of the popular Data Engineering Podcast.
This book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will benefit from the wisdom and first hand experiences of their peers.
The Data Engineer is a rather new role. However, the management of data has been well known for over a generation. Data engineers tune data for use in analytics and machine learning. Today AI, Data Lakes, Predictive Analytics, and Data Science all roll up into the modern Data Engineer. This is a series of high level insights from various professionals. They work at Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn.
Readers who seek insights will certainly find this a good reference. Since the topics range widely there is a good probability you will need to keep this reference within reach. It is refreshing to see contributions crossings areas that will be new to most readers.
Admittedly, the chapter on Data Security for Data Engineers by Katharine Jarmul from Thoughtworks is certainly a must read. In addition, Privacy Is Your Problem by Stephen Bailey must be on your list. The variety of topics is also appealing, so be ready to gain insights. Their shared postings have good ideas, warnings, and best practices all melting together.