Engineering and data software are overlapping fields that work closely together. While many careers in these fields share some common paths, they also have distinct areas of expertise that make them distinct from one another.

To manage large quantities of information and data at a large scale, companies require experts to gather and prepare it for further analysis. These experts are known as data engineers. They use programming languages to create systems that take data from sources and convert it into formats that can be used by other data specialists, like data scientists and business intelligence (BI) developers.

When they design their pipelines Data engineers take into consideration how data is modeled as it is stored, protected and encoded. They may also recommend or implement strategies to improve accuracy, reliability and quality. They might, for instance assist users to seamlessly merge data by adding uniform IDs.

Once their ETL is completed, data engineers often build applications for analytics to have a peek here help other people leverage the company’s information. This can include creating visualizations that highlight important data like trends in customer and employee behavior and product performance, among more. They also create and maintain data platforms that employees can access through APIs or web-based interfaces, such as a dashboard.

To do this it is necessary to be able to operate a variety of databases and storage technologies. For example, they might employ SQL to query relational databases and tools such as Python to create more flexible and powerful ETL processes. They can also implement an NoSQL data store such as MongoDB that provides an adaptable document-based approach to data management.