Big data engineers work to understand business objectives and translate those objectives into data processing workflows. These professionals are typically responsible for gathering and processing raw data, evaluating new data sources for acquisition and integration, and designing and implementing relational databases for storage and processing.
Often reporting to the CIO at midsize companies or to the database manager at larger companies, big data engineers are in high demand and compensated well. IT staffing firm Robert Half Technology named this position one of the top-five highest-paid tech jobs of 2015, with a salary that ranges from $119,250 to $168,250.
The big data engineer salary is expected to increase again next year. According to RHT’s 2016 Technology Salary Guide, big data engineers will see an 8.9 percent increase, boosting the salary range to $129,500 to $183,500.
“Companies have come to realize the competitive advantage that your data can give you, but hiring for these positions is incredibly difficult,” says John Reed, senior executive director at RHT. “The demand for these professionals far outpaces the supply. When you can’t find qualified individuals, you need to steal them from another company. That’s driving up the compensation, too.”
Ideal candidates should demonstrate strong analytics skills and have a background in large-scale databases, specifically NoSQL, Hadoop, Hive and HBase, says Felix Fermin, recruiting manager at IT staffing firm Mondo. Big data engineers should also have extensive programming experience—ideally in Python or Java—be expert problem solvers and work collaboratively with others.
Here are five questions you can expect hiring managers to ask during the interview process and tips for answering them the right way.
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