As data sets continue to grow exponentially, Data Engineering skills become increasingly essential — standalone or as part of Data Scientists' expertise. In today's episode, Andreas Kretz details how to Learn Data Engineering.
Andreas:
• Is the Founder of Learn Data Engineering, a platform through which he’s taught over a thousand students the theory and practice of data engineering.
• Has provided countless more folks with data engineering tips and tricks through his YouTube channel, which has over 10,000 subscribers.
• Worked for ten years at the German industrial giant Bosch, including as a data engineering team lead and data lab team lead.
• Holds a Computer Science degree from the Technical University of Applied Sciences Würzburg-Schweinfurt (THWS).
• With over 100,000 followers on LinkedIn, has twice been recognized as a Top Voice for Data Science and Analytics on the platform.
Today’s episode will appeal primarily to technical listeners particularly to data scientists that are keen to develop ever-more-critical data engineering skills.
In this episode, Andreas details:
• What data engineering is and how it relates to adjacent fields like data science, software engineering, and machine learning engineering.
• Why data engineering skills become increasingly essential to data scientists and data analysts with each passing year.
• What sets Senior Data Engineers apart from junior ones.
• His general process for tackling data engineering problems.
• The must-know data-engineering tools of today as well as the emerging ones you shouldn’t miss.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.