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Data Scientist vs Data Engineer

Author: Petar Petrov

Which one is better: data scientist or data engineer? This has been a topic of debate for a while now, but there’s no definitive answer. It depends on what your goals are and what you want to do with your career. In this post, we’ll compare and contrast the two roles so you can make an informed decision about which is right for you.

Data Scientist - Larger focus on data, analytics, math, and statistics Data Engineer - Larger focus on infrastructure, architecture, tools, and code

What is the difference between a data scientist and a data engineer?

At the beginning of data science, data scientists were data engineers too. They had to understand data structures and algorithms. The difference between data engineers and data scientists is time. Data engineers needed to know computer programming languages like Python or R to do their work. Nowadays, some tools can be used by data scientists who don’t have a computer engineering background. They just need to focus on data science rather than data engineering.


There are two similarities between a data scientist and a data engineer: 1) both use machine learning algorithms 2) both work with a big amount of data


The differences between a data scientist and a data engineer are having less experience in coding, using more visualization techniques, being an expert in only one particular area of big data analytics.

What skills are needed for each job?

Data Scientists and Data Engineers are among the most in-demand professionals today. Data scientists work to transform data into information, while Data Engineers focus on extracting, storing, and analyzing data to solve problems. Despite the similarities in their roles, Data Scientists and Data Engineers have different skillsets that affect their ability to perform well in a given role. The table below summarizes this difference:

So what is the difference between a Data Scientist and Data Engineer? As opposed to Data Scientists who use their skills in statistics, predictive modeling, and other techniques to find insights within data, Data Engineers build the capability of the organization to create better solutions for their clients.

Data scientists create new algorithms while engineers build tools that make it easier to do work.

Which job pays more, the Data Scientist or the Data Engineer

A common discussion about the Data Age is if data scientists or data engineers are more in demand.

With all of the hype around big data, it would make sense that both professions pay well. A recent pay study found that pay for both positions varies greatly based on location and job responsibilities.

In Conclusion

We can say that both data scientist and data engineer are jobs that have become increasingly popular in recent years. Data scientists use their skills to analyze large sets of data, whereas a data engineer’s aim is to build systems for the storage and retrieval of information. A job as a data scientist usually pays more than being a data engineer, but there’s no way to be sure which will come out on top simply by looking at salary ranges alone since this also depends on location. Which one would you rather do? Let us know what your thoughts are!