In the software development industry, the concept of a Full Stack Developer emerged when it became clear that one person could proficiently manage multiple technologies that were tightly interconnected. This individual was responsible for data modelling, writing backend code, and front-end work. Similarly, the data industry has seen the rise of Data Engineering to do the same for data. Data Engineers build systems to make data available and usable, move it from one place to another, and perform other related tasks.
Data Engineer – Skills
The data engineer is the bridge between the data science and the software engineering world, and must have the skills to extract, transform, and load data from both sources.
Data engineers must also have the expertise to create and maintain data pipelines, build data warehouses, and develop data models to meet the needs of the business demand of Data Quality, Data Security and Data Scalability.
Technology Stack
Data engineers must be knowledgeable in various technologies to create effective data pipelines and manage the data warehouse.
The technology stack includes languages, frameworks, databases, and tools that enable the data engineer to build, monitor, and maintain the data architecture.
Popular Data Engineering Tools
