The data engineer is someone who develops, constructs, tests and maintains architectures, such as databases and large-scale processing systems. The data scientist, on the other hand, is someone who cleans, massages, and organizes (big) data.
Data Engineer either acquires a master’s degree in a data-related field or gather a good amount of experience as a Data Analyst. A Data Engineer needs to have a strong technical background with the ability to create and integrate APIs. They also need to understand data pipelining and performance optimization.Programming Complexity is low to medium to high.
The demand for big data professionals has never been higher. … First, you should know that a data science degree isn’t training for a data engineering career. Data science is heavily math-oriented.
Data engineers write code. They’re highly analytical, and are interested in data visualization. Unlike data scientists — and inspired by our more mature parent, software engineering — data engineers build tools, infrastructure, frameworks, and services.
As of June of 2023, the demand for data engineers had increased 88% year over year (source). And that’s not all! According to Statista, “The global big data market is forecasted to grow to 103 billion U.S. dollars by 2027, more than double its expected market size in” 2023.