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Data Analyst, Data Scientist, and Data Engineer Professions: What’s the Difference?

Every year, the amount of data we generate on a daily basis increases. According to Forbes, we produced 2.5 quintillion bytes of data each day in 2018, thanks to millions upon millions of social media postings, news items, financial transactions, and other sources. As businesses get more enmeshed in data, they increasingly rely on data specialists to assist them in analyzing it so that they can make critical choices. 

This work is done by several different types of specialists. In a range of organizations, data analysts, data engineers, and data scientists have a significant effect. They all enjoy math, statistics, and problem-solving, but they use their abilities in various ways. Discovering the major distinctions between data analysts, data scientists, and data engineers can assist students with a passion for data in deciding which career path is ideal for them. 

In a nutshell, data scientists conceptualise and research issues that may be solved with data, data engineers construct programming frameworks to collect and store data, and data analysts sift through data to identify its meaning. Continue reading to discover about the distinctions and similarities between data analysts, data scientists, and data engineers. 

Data Scientist Overview 

As data scientists, programmers, graphic designers, statisticians, scientists, and other professionals collaborate to identify issues that data collection and analysis may help solve. A municipal government, for example, may desire to address certain bottleneck problems at particular intersections but has yet to discover a solution. Data scientists with expertise in traffic management may develop systems that collect data from traffic signals around the city and convert it into a dynamic map of real-time traffic, showing where bottlenecks begin and end. 

Data Scientists’ Salary and Job Prospects 

Let’s take a look at how the pay for a Data Scientist in India fluctuates based on expertise. Because of the considerable association between years of work experience and higher-paying salaries, a career in data is particularly appealing to young IT personnel.  

In this part, we’ll look at how data scientist salaries increase with experience. 


  • The average entry-level data scientist income in India is 511,468 rupees per year for a recent graduate. 
  • A data scientist with 1-4 years of experience earns an average of Rs.773,442 a year in their early career. 
  • Professionals with 5 to years ’ experience are estimated to make around INR 12 to 14 lakhs per year. A mid-level data scientist gets an average of Rs1,367,306 per year. 
  • Employees with decades of expertise or managerial positions can expect to earn anywhere from INR 24 lakhs to a hefty crore annually! 
  • When a data analyst moves from the position they were assigned to a higher one, their pay improves by 50%. 

 Overview of a Data Engineer 

Data engineers are engineering-trained computer programmers who gather, transport, and store data for analysis. They create custom programs and computer frameworks to fulfill specific needs. As a result, a fundamental distinction between data engineers, data scientists, and data analysts is that engineers have extensive programming and algorithm-writing abilities. They also connect with data scientists to ensure that they understand the goals of projects and that programs are designed with each team’s goals in mind. 

For example, if a city wants to improve its traffic patterns, data engineers would collaborate with the city’s computer and data storage systems to develop a framework that allows analysts to access data from any time, place, traffic scenario or day of the week. 

 Salary and Job Prospects for Data Engineers 

 In India, the average income for a data engineer is $836,443.  

  • It can range from a low of $368k to a high of $2 million every year.  
  • Data engineers are in high demand by numerous organisations and firms, and as a result, they may expect a solid salary even during the epidemic. 
  • However, there are a few elements that influence a data engineer’s typical income. Experience, company, employment role, geography, skillset, and other considerations might all be considered. 

Overview of a Data Analyst  

Engineers and scientists create and arrange data, which data analysts interpret for a given business, organisation, or government. The analysts sort through the results and report their conclusions after the data scientists have devised the analysis methodologies and the engineers have constructed the systems to process the data. 

Data analysts would find out what the traffic patterns and data pointed to in the case of a local administration striving to enhance traffic flow. They’d look for specific spots of interest and deliver their findings to the project’s local board of overseers. 

These findings would guide the city’s choice to build traffic signals at specific intersections or change the length of lights at others, removing critical “hot spots” and reducing traffic loads at a large number of others. 

Data Analyst Salaries and Job Outlook 

The average income for a data scientist is ₹698,413. An entry-level role with less than a year of experience can usually expect to receive close to  $500,000 annually.   

A mid-level role consisting of no less than 5 to 9 years of experience can earn 1,004,082 rupees  In India. On the other hand, Senior-level roles in India earn roughly $1,700,000 per year as their skills and talents develop.  

Similarities Between Data Analysts, Data Scientists, and Data Engineers 

Data analysts, scientists, and engineers all play distinct roles in the data management chain and therefore need diverse talents, but they all have one thing in common: an analytical, problem-solving mindset. They examine a problem and choose the most effective method to implement their skills to get a result –– whether that means building a system for efficient data retrieval, asking the right questions, or analysing the data properly. Professionals in all three roles are also likely to be computer programmers. 

Data Analysts, Data Scientists, and Data Engineers: What’s the Difference?  

While the needs of these data-driven professions are similar, there are some subtle variances between them that highlight the major differences between data analysts, data scientists, and data engineers.  

Specialization in a certain skill  

In terms of their ability to think critically about data, solve issues, and deal with computer programming and data visualisation, data analysts, data scientists, and data engineers may have comparable skill sets, but each type of data professional must cultivate unique skills to stand out. As computers’ capacity to execute complicated commands and “learn” improves, data scientists must grasp machine learning and artificial intelligence (AI). Data engineers must be experienced programmers who are also familiar with storage, data processing, and network design. Meanwhile, data analysts hone their data visualisation and application abilities.  

Certifications and Education  

A bachelor’s degree is usually required for data analysts and data engineers, whereas a master’s degree is usually required for data scientists. Through courses in programming languages, statistical design, and machine learning, a personalised curriculum like TrainOn‘s online Data Science courses may help students build the knowledge and abilities needed to succeed in any of these three professions. TrainOn also provides a variety of courses for students interested in furthering their education in data science, which may lead to more expanded employment prospects. Though certificates aren’t a legal need for data professionals to operate in the sector, they may use them to demonstrate their knowledge of common data systems and programming languages, which can help them land a job. 

Data Analyst vs. Data Scientist vs. Data Engineer: Which Is Right for You? 

This data-driven world is continuously on the lookout for fresh ideas to improve the ways we collect, analyse, and use data. Data professionals help transform the way the world works by employing critical thinking and problem-solving expertise to enterprises, corporations, and governments of all kinds. Find out more about how TrainOn’s Courses can help you launch a career in this exciting world. 



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