Why Big Data Developers Are in Hot Demand in 2022?

Why Big Data Developers Are in Hot Demand in 2022?


Why Big Data Developers Are in Hot Demand in 2022?

Are you in a job market where Big Data developers are highly valued? Are you undecided about pursuing a career in Big Data? What employment alternatives will be accessible to me after Big Data? Simply spending some time reading this blog will provide you with the answers to all of these issues as well as the reasons why big data developers are in hot demands in this decade. So, let’s get into it!

Also Read – How To Hire Freelance Web Developers Who Get The Job Done?

Check out reasons why big data developers are in hot demand in 2022 as below –

1. Increase in Job Opportunities –

With technology reaching new heights, Big Data is surely becoming a buzzword and a growing demand for enterprises in the next years. However, as Jeanne Harris, a senior executive at Accenture Institute, put it, “data is useless unless you know how to interpret it.”

Big Data professionals are in high demand in enterprises all over the world today. To keep ahead of the competition, businesses are making extensive use of Big Data. Candidates with Big Data expertise and talents are in high demand. According to IBM, the number of data professionals in the United States will grow to 2,720,000 by 2020.

2. High Salaries –

Wages for competent experts are being affected by the high demand for Big Data professionals. According to Glassdoor, the following are the salaries offered by various organizations based on employees working in these organizations in the US region:


Big Data experts’ salaries are directly related to aspects such as their talents, education, domain expertise, technological understanding, and so on. In addition, one must understand and solve real-world Big Data problems, as well as have a solid understanding of tools and technology.

3. Massive Big Data Adoption –

According to Forbes, big data use in organizations has risen from 17 percent in 2015 to 59 percent in 2018, with a compound annual growth rate (CAGR) of 36 percent. Big Data is steadily spreading its wings over a wide range of industries, including sales, marketing, R&D, logistics, strategic management, and so on.

According to Intel’s ‘Peer Research – Big Data Analytics’ survey, Big Data is one of the top priorities of the firms participating in the survey because they believe it improves the performance of their organizations. According to the survey, 45 percent of respondents believe that Big Data would provide greater business benefits, propelling them to the top of the Big Data industry.

4. High Variation in Job Titles and Responsibilities –

Big Data workers can choose from a variety of job titles based on their previous experience. There are numerous possibilities for Big Data job seekers, and they are free to align their career pathways based on their employment preferences. The following are some of the job roles that Big Data specialists can hold:

  • Data Engineer
  • Business Analyst
  • Visualization Specialist
  • Machine Learning Expert
  • Analytics Consultant
  • Solution Architect
  • Big Data Solution Architect
  • Big Data Analyst

5. Usage Across Numerous Firms –


Big Data is now employed in practically every business. Professional, Scientific, and Technical Services (27 percent), Information Technology (19 percent), Manufacturing (15 percent), Finance and Insurance (9 percent), Retail Trade (9 percent), and Others (21 percent) are the top five industries that are actively seeking Big Data professionals.

The Career Path of a Big Data Professional –

  • Data Scientist
  • Big Data Engineer
  • Big Data Analyst
  • Data Visualization Developer
  • Machine Learning Engineer
  • Business Intelligence Engineer
  • Business Analytics Specialist
  • Machine Learning Scientist

Let’s talk about each career in detail.


1. Data Scientist –

This is the most looked for job path among Big Data professionals. Data Scientists are those who use their technical and analytical abilities to extract meaning from data. They are in charge of gathering, cleansing, and modifying data.

2. Big Data Engineer –

Big Data Engineer is a well-known and challenging job path. Data Engineers are the individuals in charge of constructing the designs created by Solution Architects. They are in charge of designing, testing, administering, and supporting big data solutions in businesses.

3. Big Data Analyst –

Data Analysts find important information from datasets using their knowledge of big data technologies such as Hadoop, Hive, Pig, and others, as well as their analytical skills. This is also the most difficult aspect of a Big Data career.

4. Data Visualization Developer –

Data visualization developers are in charge of creating, envisioning, developing graphics or data visualization, and supporting data visualization activities. They must have good technical abilities in order to use tools to implement visualization.

5. Machine Learning Engineer –

Machine Learning is now an essential skill of Big Data developers. As a machine learning specialist (Machine Learning Engineer), you will be in charge of developing data analysis software that will allow the product code to function without the need for human involvement.

6. Business Intelligence Engineer –

According to a Forbes research, 90 percent of IT professionals aim to boost their spending on BI technologies, putting Business Intelligence Engineers in high demand. BI engineers are in charge of maintaining large data warehouses using Big Data tools and resolving difficult Big Data issues.

7. Business Analytics Specialist –

A Business Analytics Specialist is an expert in the field of Business Analytics who assists in the development of scripts to test scripts and the execution of testing. They are also in charge of conducting business research in order to identify problems and propose cost-effective solutions.

8. Machine Learning Scientist –

Machine Learning Scientists are most likely employed in the R&D department. They are in charge of creating algorithms for usage in adaptive systems, as well as adding product proposals and anticipating demand for the same.

Also Read – Software Engineers And Developers: Putting Technology at Our Fingertips


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