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Software for data engineering and engineering overlap and work closely together. While many careers in these fields follow similar paths, they have different areas of expertise that distinguish them from one another.

To manage large quantities of data and information at scale, companies need experts to manage the task of collecting and preparing it for further analysis. These specialists are known as data engineers. They use programming languages to design systems that gather data and convert it into formats useful for other data specialists – such as data scientists or business intelligence (BI) developers.

Data engineers think about how data is stored encrypted, protected, and stored when they design their pipelines. They can recommend or implement ways to improve data reliability, efficiency, and quality. They could, for instance, help end users seamlessly integrate data by adding uniform IDs.

Data engineers often develop analytics applications after their ETL is complete to help others utilize company information. This includes the creation of visualizations to highlight important data, such as employee and customer trends or product performance, and more. They also develop and maintain data platforms, which employees can access via APIs or web interfaces like dashboards.

To do this, they should be able to manage a variety of storage and databases. For example, they might use SQL to query relational databases and tools like Python to create more flexible and robust ETL processes. Or, they could implement an NoSQL database, such as MongoDB with a more flexible approach to document-based approaches to data management.