The upsurge of data being generated and the need for its analysis have led to an urgent demand for talent in the data space. This brings an opportunity for data enthusiasts to explore and become highly in-demand data professionals. According to Randstad’s Study, everything about the world of work has changed drastically since early 2020. Employers are still struggling to find talent for key roles including AI, machine learning, data engineering, data science, and more.

In part 1 of this article, I discussed how you can become an in-demand data professional from the perspective of our Engineers at Data2Bots. The article was rich with information from my discussion with current professionals in the field.

In this article, you will get to know the current trends, and opportunities in the data space and how you can upskill to become an in-demand data expert. You will also see how you can fill the data gap in the data field in terms of the skills required and how you can learn them.

Data Professionals Job Trends

According to IBM, there was an increase in data-related job openings from 364,000 to 2,720,000 in the year 2020. So, there will be a sharp increase in demand for data professionals by 2022. This demand will only grow further to an astonishing 700,000 openings.

In another research, the data space is predicted to grow over the next decade. The demand for data scientists and other related professionals rose by 28% by 2020 alone. It is an astonishing fact that close to 90% of the data in the world was generated in just 2 years. How can you then imagine the amount of data that will be generated in the next decade?

In the LinkedIn 2020 reports, data is another field that has topped the Emerging Jobs list for three years running. It’s a speciality that is continuing to grow significantly across all industries. The report indicated that some of this growth can likely be attributed to the evolution of previously existing jobs, like Statisticians, and increased emphasis on data in academic research.

Data related jobs such as data engineering, data analysis and data architecture, are the top positions listed on the Glassdoor website. These positions will likely remain unchanged in the future. It was also reported that the data related openings are open for 45 days. This figure is 5 days more than the ones in a regular job market.

How to Acquire the Required Skills to Become a Data Professional

Data Professionals such as data engineers, data scientists and data analysts required distinct but similar skills which include Programming Language (Python, Java, Scala), Data Processes, Machine learning, data visualisation, Presentation skill, critical thinking among others.

Different kinds of certifications exist for each career path in the data profession. The certification includes but is not limited to:

• Certified Analytics Professional (CAP)
• Cloudera Certified Associate (CCA) Data Analyst
• Cloudera Certified Professional (CCP) Data Engineer
• Data Science Council of America (DASCA) Senior Data Scientist (SDS)
• Dell EMC Data Science Track (EMCDS)
• Google Professional Data Engineer Certification
• IBM Data Science Professional Certificate
• Microsoft Certified: Azure Data Scientist Associate
• SAS Certified AI & Machine Learning Professional

Apart from Universities programs on data science and engineering leading to the award of degree certification. Companies such as IBM, Google, and Microsoft have courses that train and certify qualified professionals. There are also some online courses offered by other online vendors like Coursera. Another option available is to attend a well structured upskill program such as Data2Bots Academy upskill program leading to certification, job placement, and relocation. Data2Bots Academy offers a 9-month intensive, well structured and career-focused upskill program that takes you from zero to mastery in the data field such as Data Engineering, Machine Learning Engineering, Analytics Engineering etc.

Data Professionals Salaries

According to Glassdoor, data professionals’ average salary is $105,601 /yr. This number represents the median, which is the midpoint of the ranges from their proprietary total pay estimate model and based on salaries collected from their users. 

The average salary for the role of data analyst according to LinkedIn is $65,000. While a data engineer earned $156,008 per year, the average data scientist’s earning is $154,002 annually. Also, the average remuneration for a machine learning engineer is $125,000 per year.

Data Professionals Average Salary

Conclusion

Data roles are at the forefront of the job openings across all job sites. If you want to become a data professional in a short period of time, then you must check the Data2Bots Academy upskill programme. Data2Bot Academy provides you with the most efficient and supportive way to upskill and become the top 10%, in demand data professionals. Register today and get access to early bird perks.This is a sample post