Data engineers design and build the necessary infrastructure to prepare raw data for analysis. They are creators, organizers, and contributors who leverage a variety of big data technologies to create free-flowing data pipelines that enable real-time analytics. Data engineers aren’t responsible for the operation of all computing systems within a company, just the parts of the system related to the data pipeline. Their primary goal is to help data scientists turn raw data into valuable and actionable insights.
They must have a multitude of technical skills to help them creatively solve complex problems – such as advanced knowledge of programming languages like Python, R, and Scala; database management systems languages like SQL; and cloud computing services like AWS and GCP. Teamwork and communication are a must, as well as being analytical, organized. and detailed.
About half of data engineers come from a software engineering background, and becoming one generally requires a bachelor’s degree in computer science, information technology, applied math or statistics, plus a formal data engineering certification like the ones offered by Google or IBM. As companies exponentially invest in data transformational projects, data engineers are in extremely high demand – and the broad yet highly specialized and constantly evolving skills needed to handle sprawling data infrastructures makes finding them very difficult. Data engineering is listed as the fastest growing tech occupation based on year-over-year growth, with growth estimates through 2025 ranging from 18-31%.