Software for data engineering and engineering are closely linked and overlap. Although the careers in these fields have some similarities however, they also have their own areas of expertise which make them distinct.

To manage huge amounts of information and data at a large scale, businesses require experts to take care of preparing and collecting it for further analysis. These experts are referred to as data engineers. Data engineers use programming languages to create systems that source data transform it into data and make it useful for other specialists in data, such as Data scientists and Business Intelligence (BI) developers.

Data engineers think about the way data is stored and encoded, as well as how it is secured when they design their pipelines. They could also suggest or implement methods to increase accuracy, reliability and quality. They can, for example, help end users seamlessly integrate data by adding uniform IDs.

Data engineers typically create analytics applications once their ETL is completed to assist others utilize company information. This can include making visualizations that highlight crucial data points such as employee and customer trends or product performance. They also design and manage data platforms that employees can access via APIs or web interfaces, such as dashboards.

To do so it is necessary to be able to use a variety of databases and storage technologies. For instance, they could using SQL to query relational database and a program like Python to create more flexible and efficient ETL processes. They can also implement a NoSQL data store, such as MongoDB that provides a flexible document-based approach for managing data.