Big data engineers are in huge demand in the Information Technology sector. The industry is facing a shortage of quality big data engineers. That’s why the salary and employment prospects for employees in this profession are also pretty high.
Big Data adoption by companies is happening on a large scale. This technology is deeply integrated into many organizations and is needed for various services and systems. So, this automatically translates into a surge in demand for big data engineers. Indeed, there is a huge potential for making big bucks if you are a trained and qualified big data engineer.
Many reports point to data engineering as the fastest-growing technology job globally. Likewise, there can be a 50 percent year-over-year growth in the number of big data engineer job openings in the coming years.
What Is Big Data Engineering?
Big data engineers are responsible for the data management of an enterprise. They develop, maintain, test, analyze, and evaluate a company’s data. Big data is the huge volumes of data flowing in from diverse sources in various forms in the course of business operations. The big data engineer is in charge of processing systems and databases. They know how to extract data and convert them into workable formats. The converted data offers valuable information for improving the company’s operations, efficiency, and bottom line.
Salary of a Big Data Engineer
The average salary of big data engineers working in the United States is around $109,000. The salaries are influenced by various factors such as industry, location, experience, and specialization. Some popular job boards have shared the following average salary estimate for a big data engineer.
- Glassdoor – $109,506
- Salary.com $123,089
- ZipRecruiter $130674
- Payscale $93,269
Factors Influencing Salaries of Big Data Engineers
The salary of big data scientists is also impacted by where they work and live in the United States. Employees in big cities get a higher salary to cover the higher cost of living in these places. Indeed, with companies continuing to use a more remote workforce, few offer location-based salaries.
Salaries may also differ depending on the nationality of the engineer and the country they choose to work from. Digital nomadism is on the rise in the tech industry. Most companies in the US still do not allow employees from another country to work permanently.
Big Data Engineer Salaries by Industry
Nearly every industry leverages the use of big data. This has resulted in massive demand for qualified and experienced engineers. Companies also need their expertise to harness the vast volumes of data they receive daily and drive efficient decision-making. However, every industry offers a different pay scale to big data engineers.
Knowing the salaries offered by various industries can help you make the right career move. Likewise, you can plan your career by aiming for a job with a decent salary. Technology companies top the chart in big data engineer’s salaries. Moreover, there are other popular industries where big data engineers can expect a good salary. These are finance, insurance, science and technology, manufacturing, management, etc. Also, these industries account for more than 75 percent of data-related job openings in the US. There is a high demand for data science skills in all these industries.
Big Data Engineer Salaries by Experience
The experience of big data engineers is one of the most significant factors influencing their salaries. This is common in all professions. However, for big data engineers, the more they learn, the more they are likely to earn.
Here’s how experience can impact a big data engineer’s salary:
- Experience: 2-4 years, Designation: Data Engineer, Salary: $114,196
- Experience 5-7 years, Designation: Lead Data Engineer, Salary: $149,520
- Experience 8+ years, Designation: Principal Data Engineer, Salary: $167,083
- Experience 8 – 10 years, Position: Director of Data Engineering, Salary: $201,657
- Experience: 10+ years, Position: Vice President, Salary: $202,595
A job title in any of the above roles with a ‘Senior’ tagged to it can make a huge difference. It can certainly add a few thousand dollars more to your salary.
Big data engineers start their careers in entry-level positions with job titles such as business analysts, data analysts, or software engineers. As they gain experience, they are accepted into managerial positions. They become big data engineers and then make progress to a larger salary and employment prospects as they gain experience.
Salaries for Other Big Data and Engineering Professionals
Ample job opportunities exist for those who specialize in data management. Companies in the US offer different roles and positions for data engineers. Likewise, some of the hottest jobs in the IT industry at present for data engineers and the corresponding average salaries:
- Data analyst: $62,364
- Business intelligence analyst: $72,224
- Business analyst: $77,682
- Database administrator: $82,838
- Data engineer: $92.179
- Software engineer: $101,910
- Data scientist: $104,537
- Machine learning engineer: $107,566
- Data architect: $129,183
Employment Prospect for Big Data Engineers
Big data is the buzzword not only in IT but across all many other industries. Even the government and its related administrative services use big data to drive efficiency and make informed business decisions.
According to The Bureau of Labor Statistics (BLS), big data engineers are categorized as statisticians and computer and information research scientists. Additionally, the projected job growth in these categories is 33 percent and 22 percent, respectively, for 2020-30.
The Future of Jobs 2020 Report, based on a survey by the World Economic Forum, has some interesting data to share. The survey covered over 80 percent of the companies. Moreover, in the report, a big data engineer is ranked third for jobs with growing demand across various industries.
A prospective big data engineer must master specialized technical skills for a large salary and employment prospects. These include:
Computer languages like C++, Java, and Python, OS skills such as Unix, Solaris, and Linux. Skills in other specializations like Hadoop, Apache Spark, data mining, and SQL are equally desirable. You can improve the prospects of working for reputed companies by getting bachelor’s and master’s degrees in computer science, statistics, and analytics. Getting additional professional certifications is also recommended.