Data science is now one of the most influential topics all around. Companies and enterprises are focusing a lot on gathering data science talent further creating more viable roles in the data science industry. It has also been stated that data science and data scientistare the two most popular career tracks as of now.
Since the advent of big data industry, the roles were very blurred since the main objective was to get the insights. But due to a recent change in perspectives, a lot has been written about the difference between the different data science roles, and more specifically about the difference between data scientists and data engineers.
The role of the data scientist and that of a data engineer will now be discussed thoroughly with intricacy.
Work and Responsibilities
Data engineer’s responsibilities
A data engineer is he/she who indulges in the art of construction, development, and maintaining the architecture of databases and large-scale processing systems. They also have to deal with working along with all sorts of raw data which contain all sorts of errors. These data contains codes that are system-specific, and unformatted. It is up to the data engineer to implement ways to improve data reliability, efficiency, and quality. The data engineer must improvise and be aware of the opportunities in order to fetch data which gets procured constantly. This information will, in turn, be processed as data for the scientists to work on. They are also responsible for taking care of the architecture that supports the scientists. So that the data set is possible to be mined, modeled and used for other production purposes.