All analytics is data engineering. Manipulating data content in context to achieve useful results, using a proven process.
A Data Engineer's Guide To Non-Traditional Data Storage by Irina Papuc:
With the rise of and data science, many engineering roles are being challenged and expanded. ...
Originally, the purpose of data engineering was the loading of external data sources and the designing of databases (designing and developing pipelines to collect, manipulate, store, and analyze data).
It has since grown to support the volume and complexity of big data. So data engineering now encapsulates a wide range of skills, from web-crawling, data cleansing, distributed computing, and data storage and retrieval.
For data engineering and data engineers, data storage and retrieval is the critical component of the pipeline together with how the data can be used and analyzed. ... "