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A data engineer works with sets of data to advance data science goals. Unlike other roles, such as a data scientist, a data engineer is not generally as involved in overall strategic analysis, but more deeply involved in working hands-on with the data sets.
Data engineers work with the life cycle of data sets to help make data useful to a project. Many are primarily interested in aggregating raw data and making it into useful, ordered and structured data formats. For example, a project may involve sourcing data from a variety of edge computing locations, running it through middleware into a central repository, refining that data and cleaning it up, and outputting it in a very precise format for use in artificial intelligence and machine learning systems. Here, the data engineer would be primarily involved in looking at how that data is acquired, how that data is refined, and how it moves through the pipeline, as well as ensuring companies wind up with the right data assets. Data security and data governance also affect the work of a data engineer. In general, data engineers are widely in demand since data is becoming one of the average business’s best assets.