Data engineering is the practice designing and building systems for collecting, storing, and analyzing data at scale. It is a broad field with applications in just about every industry. Organizations have the ability to collect massive amounts of data, and they need the right people and technology to ensure the data is in a highly usable state by the time it reaches the data scientists and analysts.

This article elaborates the Data Engineer into further necessary information as it is originated from source and adapted from IBM.

In addition to making the lives of data scientists easier, working as a data engineer can give you the opportunity to make a tangible difference in a world where we’ll be producing 463 exabytes per day by 2025. That’s one and 18 zeros of bytes worth of data. Fields like machine learning and deep learning can’t succeed without data engineers to process and channel that data.

What does a data engineer do?

Data engineers work in a variety of settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. Their ultimate goal is to make data accessible so that organizations can use it to evaluate and optimize their performance.