Data engineers and data scientists are two distinct roles involved in managing and analyzing data, though there can be some overlap between their responsibilities.
Data engineers generally focus on the development and maintenance of data systems, with a strong emphasis on technical skills. They are responsible for designing, building, and maintaining the data infrastructure that enables efficient and secure data storage, retrieval, and processing. In their day-to-day work, data engineers deal with issues such as designing data architectures, building pipelines to move and transform data, and maintaining databases, servers, and other infrastructure.
On the other hand, data scientists focus on analyzing data to gain insights and inform business decisions. They are responsible for applying statistical and machine learning techniques to large data sets, developing models, and communicating insights to stakeholders in a clear, accessible way. In their day-to-day, data scientists work on tasks such as data exploration, mining, and cleaning, developing algorithms and models, and presenting insights and recommendations to decision-makers.
Overall, data engineers tend to be more focused on data infrastructure, while data scientists focus on data analysis and interpretation. Both roles are essential to any organization that deals with large amounts of data and require different skill sets, though there can be some overlap between their responsibilities.