Do you know that the global data volume will reach 175 zettabytes in 2025? Now, that’s enormous data literally. But the data will make sense only when it is processed and analyzed through frameworks. This is where a Big Data Engineer comes into the spotlight.
“Every company has big data in its future, and every company will eventually be in the data business.”
Thomas H.Davenport, of Saïd Business School, University of Oxford
Big Data Engineers are ubiquitous in every data-driven industry from agriculture to climate change. So, technical recruiters should have a keen eye for data wizards who have a flair for numbers and coding.
A Big Data Engineer is an IT professional who designs, builds, tests, and maintains complex data processing systems that work in tandem with large data volumes.
On any given day, you can see a Big Data Engineer performing the roles of software developers, coding, data scientists, statisticians, and engineers simultaneously.
Global Big Data market revenues for software and services are forecasted to reach $103 bn by 2027, with a CAGR of 10.48%, reports Wikibon
Conjunctively, Forbes adds that,
Jobs in Machine Learning Engineering, Data Science, and Big Data Engineering are among the top emerging jobs on LinkedIn.
So, companies should embrace big data to avoid losing their competitive position or worse, facing extinction.
The U.S.Bureau of Labor Statistics predicts the growth of the Big Data Engineer job market at 22% through 2030.
Recommended Read: Hiring a Data Architect
As per Glassdoor estimates, the national average for a Big Data Engineer salary in the USA is $1,04,463 per year, with an added compensation between $2,342 – $30,427.
Here are the KPIs to measure a Big Data Engineer’s work potential:
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