How to become a Data Engineer – A Complete Career Guide
Data science is the fastest-growing industry in the world right now, and data engineers are right there at the front of the pack. With perhaps the best job outlook of all data science roles (and that is saying something), pursuing a data engineering role is absolutely one to consider and Discover Data Science is here to let you know what it takes to make that role yours.
Data engineers are necessary in the big data revolution to build, test, and maintain data architecture. They are closely linked with data architects—in fact, these two positions must collaborate on most projects. You can consider the relationship similar to that of a real-world architect and engineer, an architect can design a beautiful building, but it’ll take an engineer to actually build it. Data engineers focus on the construction of systems that can house massive amounts of data. The architecture that a data engineer builds allows a data scientist to easily pull relevant data sets for analysis.
What is a Data Engineer?
Data engineers build and maintain data pipelines, warehousing big data in such a way that makes it accessible later on. This infrastructure is necessary for every other aspect of data science. The data engineer develops, constructs, maintains, and tests architecture, including databases and large-scale processing systems. The data set processes that data engineers build are then used in modeling, mining, acquisition, and verification.
The data engineer works in tandem with data architects, data analysts, and data scientists. Data architects are in charge of data management systems, and understand a company’s data use, while data analysts interpret data to develop actionable insights. Finally, data scientists focus on machine learning and advanced statistical modeling. They must share these insights to other stakeholders in the company through data visualization and storytelling.
What does a Data Engineer do?
The data engineer is chiefly in charge of designing, building, testing, and maintaining data management systems. This allows the generation of applicable data for specific projects. To do this, data engineers must have a strong command of common scripting languages. They must solve complex problems on a coding level.
Note that data engineers are the builders of data systems, and not those who mine it for insights. The data engineer thus works more “behind-the-scenes” and must be comfortable with other members of the team producing business solutions from this data. Data engineers are also responsible for monitoring the movement and status of data in the systems that they develop, which can involve categorizing and cleaning large datasets when they become available.
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|School Name||Level||Program||More Info|
|Georgetown University||Master||Master of Science in Business Analytics||Website|
|Concordia University, St. Paul||Master||Master of Science in Data Analytics||Website|
|Johns Hopkins||Master||Online MS in Data Analytics and Policy||Website|
|George Mason University||Master||Online MS in Data Analytics Engineering||Website|
|Utica College||Master||Online MS in Data Science||Website|
|Capella University||Bachelor||B.S. in Data Analytics||Website|
|Southern New Hampshire University||Bachelor||B.S. in Data Analytics||Website|
|University of Scranton||Master||Online MS in Business Analytics||Website|
|Drake University||Master||Online Master of Data Analytics||Website|
|Northern Illinois University||Master||Online Master of Science in Data Analytics||Website|