What are you trying to automate? Model building? If so are you trying to make it easy for a business operations person to build their own models without help from a data scientist? Or are you trying to automate the conversion of models into production workflows that integrate with other enterprise applications? That is data engineering.
What are you trying to optimize? My time in doing analysis? Trying to guide analysis down useful paths and eliminate dead ends with features that are not actually helpful?
What do you include in your domain of data science? Sometimes people reduce it to neural networks deep learning architectures. Others include all types of statistical learning. Others include NLP. While others might focus on IoT of time series analysis. At least in part tools are tied to the specific subset of the data science domain that a person is working within.