What is the Difference Between a Data Scientist and a Data Engineer

what-is-the-difference-between-a-data-scientist-and-a-data-engineer

There are many job titles that get confused with each other, such as web designer and web developer. This can be confusing if you are searching for the right job to suit your skills. Two jobs where there is often some discussion about how they differ are a data scientist and data engineer.

If you have qualified from an IT course, or you are already working in the industry, you may be interested in these roles; for now, or for the future. So what exactly is the difference between a data scientist and a data engineer?

The Role Of a Data Scientist


Most data scientists have an academic background, in a subject such as maths, physics or statistics. This may not be the perfect role for someone who is IT focussed with their skills. Having said that, many data scientists find it necessary to learn a certain amount of programming, in order for them to carry out their work effectively.

This work involves understanding how data patterns work and what they mean. Analysis skills are essential to the role. Although much of a data scientist's work is based around theory, there are some practical requirements. For instance, some data scientists produce forms of artificial intelligence and all data scientists need to be able to effectively communicate their findings and provide advice about real-world implications.

The Role of a Data Engineer


Data engineers are quite different from their data scientist colleagues. They have advanced programming skills and use languages like Python and Java. They are in charge of the practical considerations of managing and using big data. They create software that enables big data solutions that are informed by the findings of data scientists.

Can One Person Do Both Jobs?


Some companies try to get one person to undertake the role of a data scientist and data engineer. This is mostly due to financial considerations. However, the roles are actually very different from each other, and it's often not possible for one person to do them both. When this does happen effectively, it's usually a data scientist that has had to take on engineering work; not the other way round.

Ideally, companies should have a single data scientist for every two data engineers, in order to ensure that its data pipeline functions efficiently and that it makes the best use of the big data that is available.

If you are looking to work in the world of big data, you need to decide which role you are best suited for. Generally, for anyone who has an IT and programming background, a data engineer is the preferred role. Experience and knowledge are more important than qualifications for this role. Whereas, the role of a data scientist is more academic, and more often than not people who undertake this role have a university background. The two roles do occasionally have some overlap when solutions are being developed, but they mostly complement each other.

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