Data Engineer Vs. Data Scientist, What's The Difference?

A data engineer and data scientist are the two most popular roles in the field of data science. The key differences in their duties and job roles have been explained in this article.

Data engineer & Data scientist: Many people think that data engineers and data scientists do the same set of tasks and activities on a daily basis. However, there are various differences between the job roles of data engineer and data scientist. A data engineer cleans the raw data and prepares it for further processing. A data scientist extracts insights from the data produced by the data engineer. We will take a deeper look at the differences between data engineer and data scientist in the below sections.

Table of Contents

Data Engineer Vs. Data Scientist, An Overview

As the duties and job roles of data engineers and data scientists vary greatly, the skills they require to fulfill their duties also differ. An overview of the differences between data engineer and data scientist is provided in the below table:

Data Engineer Vs. Data Scientist, An Overview
Particulars	Details
Data Engineering Pillars	Data Pipelines, Big Data Storage, ETL (Extract, Transform, Load) Model
Data Science Pillars	Statistics, machine learning, and data analytical skills.
Who earns more? Data Engineer or Data Scientist	Data Scientist
Data Science Courses	BSc Data Science, B. Tech Data Science, M. Tech Data Science, MSc Data Science
Data Engineering Courses	BSc Computer Science, Software Engineering, B. Tech in IT, etc.

Who Is a Data Engineer?

Data collected from various websites, forums, and other sources is usually available in an unstructured format. Also, different types of data like videos, photos, reviews, reels, etc. are available on the internet. So, to categorize the data and structure it, we need a specialist. That specialist is a data engineer.

The basic tasks of a data engineer is to collect and integrate data from various sources. The raw data is then cleaned and corrected to get a complete and high-quality data. They use different tools and applications to organize and sort the data.

They must know about the Big Data technologies to manipulate the data and create free-flowing data pipelines. They must have knowledge of database languages like SQL, Oracle, etc. At the same time, they should also be proficient in processing data using various applications and programming languages.

Who Is A Data Scientist?

A data scientist uses the data obtained from data engineers to draw meaningful insights. The insights are then used to make critical business decisions. Data scientists have to process and interpret large chunks of data. So, they usually rely on machine learning models and AI (Artificial Intelligence) tools. They know how to use statistical models to prepare the data and build prescriptive and predictive analysis models.

The basic duty of a data scientist is to identify trends and patterns from huge datasets. They examine both internal and external data sources while extracting insights. So, they have a prominent role in making business decisions. Their job roles involve extensive research and use of sophisticated tools like MS Excel, Tableau, NumPy, etc. They must also possess knowledge of programming languages like R, Python, SAS, and more.

Along with data processing, data scientists also acquire skills to manipulate and present the data. They use various data visualizations tools and techniques to present the data graphically. It is so because they must make the data insights understandable for all the stakeholders of the company. So, their duties are critical for the success of their respective organizations.

Also read: Data Scientist vs Data Analyst vs Data Engineer

Differences Between Data Engineer & Data Scientist

Now, let’s look at the key differences between data engineers and data scientists:

Differences Between Data Engineer and Data Scientist
Sr. No.	Data Engineer	Data Scientist
1	A data engineer collects data from various sources and integrates them to create unified data.	A data scientist analyzes the data and draws meaningful conclusions from it.
2	Data engineers identify the right sources of data as per the business needs.	Data scientists examine the data closely to unveil trends and patterns.
3	Data engineers are not dependent on anyone for rendering their duties.	Data scientists must rely on data engineers to provide quality data.
4	Data engineers have no role in the decision-making process.	Decisions are based on the insights provided by data scientists. So, their role in the decision-making process is critical.
5	Some of the skills required to become a data engineer include data warehousing, machine learning, data architecture knowledge, and more. The data engineers must also possess knowledge of programming languages like SQL, Hadoop, etc.	Data scientists must have advanced skills and knowledge to process, analyze, and present the data. They must have a strong understanding of data visualization methods and applications. Knowledge of programming languages like R and Python is also a must for them. They must know how to perform statistical analysis using AI, machine learning, and other technologies. Data scientists have extensive knowledge of applications like Apache Spark, MS Excel, etc.
6	Data engineers are held responsible for maintaining the quality and accuracy of the data.	The job of data scientists is to use the data to establish a stronger relationship between a company and its customers.
7	Data engineers handle raw and unstructured data.	Data scientists handle refined and manipulated data provided by data engineers.
8	The average annual salary of data engineers in India is approximately Rs. 9,80,000.	The average salary of data scientists in India is approximately Rs. 12,20,000.
9	Data engineers must possess technical skills to refine and correct the data.	Along with technical skills, data scientists must also possess storytelling skills to convey the meaning of data to various stakeholders of the business.
10	Data engineers recommend methods to enhance quality, efficiency, and reliability of the data.	Data scientists present the data using data visualization tools.
11	Data engineers develop practices for mining, collecting, and modeling data.	Data scientists explore the data and prepare it for predictive analysis.

From the above comparison, it is evident that the job roles and duties of data engineers and data scientists vary greatly. However, their duties are interconnected and complement each other. They also have some commonalities among them. For example, both have a background in data science or computer science.

In the business world, data scientists have more business intelligence and acumen. It is so because they participate in the decision-making process and have a strong understanding of emerging trends and patterns in the data. On the other hand, data engineers don’t possess a strong business acumen. It is so because their job is to prepare and process the data to remove anomalies and inconsistencies from it. Yet, both these job roles require a wide range of professional skills and knowledge.

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Data Engineer vs. Data Scientist (FAQs)

Which is better: data scientist or data engineer?

Both data scientists and data engineers have their specific job roles and duties. If you want a senior role like team leader, it is better to seek courses to become a data scientist. However, if you want to work as an entry-level data engineer or analyst, it is better to go for the respective courses.

Does data engineering require coding?

Coding is a compulsory skill for all the data engineers. They must have knowledge about SQL, Hadoop, and other programming languages.

Who gets a higher salary: data engineer or data scientist?

Data scientists have a higher salary than data engineers. Though the difference in the monthly salaries is not too much, the overall difference in the yearly package is quite a bit.

Which is a difficult job, data engineer or data scientist?

It is easier to become a data engineer if you acquire all the technical skills required to complete the daily tasks. However, if you have strong analytical skills accompanied with fluent communication, you can be a good data scientist.

Can I be both a data scientist and data engineer?

The diverse duties of data scientists and data engineers make it practically impossible to manage both the roles together. However, those who are skilled in both data engineering and data science manage both the job roles without any issues.

Is Java compulsory for data engineers?

Data engineers have to be proficient in any one language from Python, Scala, and Java.

Do data engineers need ML?

Data engineers have a basic understanding of data flows and models. However, they are not proficient in machine learning and statistical models like data scientists.

Can I become a data scientist by IIT?

Yes, you can apply for the BSc Data Science course in any IIT. Once you complete this course, you will have the credentials in your portfolio that can help you become a data scientist in any organization.

Does data scientist have a future?

Data scientists are always in huge demand because of the wide range of data analytical roles and duties they perform daily. The demand will grow in the future as companies will start relying on data for all the business decisions.

Which is more in demand: data engineer or data scientist?

Data engineers and data scientists have a huge demand in the market. MNCs like Google, Amazon, Meta, Microsoft, etc. are the companies that offer the best salaries in the industry for these two roles.