Data and engineering software are two different fields that work closely together. While many careers within these fields have some common pathways, they have distinct areas of expertise that differentiate them from one another.

To manage large amounts of information and data at a large scale, companies require experts to gather and organize it for further analysis. These specialized experts are called data engineers. Data engineers employ programming languages to build systems that take data from sources transform it into data and make it more useful to other data specialists like data scientists and Business Intelligence (BI) developers.

When they design their pipelines Data engineers look at how data is structured as it is stored, protected and encoded. They might also suggest or implement strategies to improve data reliability, efficiency, and quality. For instance, they can aid in the integration of data from different systems by adding uniform IDs that allow users to seamlessly merge information.

Data engineers often develop analytics applications after their ETL is completed to assist others utilize company information. This includes developing visualizations that highlight key data points like trends for employees and customers, product performance, and more. They also create and maintain data platforms which employees can access via APIs or web-based interfaces, such as a dashboard.

To do this, they must be able to manage several storage and databases. For example, they might employ SQL to query relational databases as well as tools such as Python for more flexible and robust ETL processes. Alternately, they could use an NoSQL database, such as MongoDB with a more flexible document-based approach to managing data.