There is no doubt that a data engineer is equipped with the necessary technical skills and acumen to become a good data scientist – but there is no guarantee to it as the primary skillsets of a data scientist is not only to engineer or transform data but to model it in a way that actionable and relevant insights can be drawn from the data.
The advantage that a data engineer has in the quest of becoming a data scientist over and above other candidates is that they would have a better know-how of data and would be able to identify anomaly must faster than other candidates.
Of course! You do have to be mindful of a couple of things, though:
The skill sets of these two differ slightly, which means that you’ll need to pay some attention to learning (quite) a lot more about mathematics and statistics, for example. This mostly depends on your previous background, of course, but since a data scientist position usually focuses on different things, you’ll see that you’ll probably want to learn more about data visualization, too, for example.
In accordance with your skill set, you’ll see that you probably also want to focus on other tools as well, such as R, SAS, Tableau, pandas, etc.