What Is Data Engineer?

Data engineers are the unsung heroes of data science. They're less famous than data scientists, but they do all the heavy lifting. A data engineer is a master of manipulating sets of data. They're like a super-engineer for your information: they can take your raw data and turn it into something useful for your business (and maybe even yourself). Like other roles in data science, such as a data scientist or an analyst, a data engineer works with the basic data set. Unlike the different functions, they aren't generally involved in the strategic analysis or making big decisions about where to go with the company's goals; instead, they focus on getting their hands dirty and making sure every piece of data is in place so that when it comes time to analyze it, everything is ready to go! As a data engineer, you're responsible for ensuring that companies and other organizations have access to the correct data at the right time. That's right: you're responsible for making sure your company has everything they need to make its projects successful. You do this by working with raw data and turning it into usable, ordered and structured formats. For instance, you serve at a company specializing in artificial intelligence and machine learning systems. Your team needs to know where to find edge computing locations to acquire certain types of raw data—so you contact suppliers and start sourcing them. Then, once you receive the data from these various locations, you'll run it through middleware into a central repository so all your team members can access it. Once it's in there, you'll refine that data, clean it up so it's ready for AI s, and then output it in just the proper format so your company can use it as effectively as possible. In addition to ensuring that companies have access to all their needed assets, data engineers must ensure they are secure. Data is becoming one of businesses most valuable assets—so protecting that information should be a top priority!