As the use of big data expands, the demand is growing for professionals who can design the systems and network architecture that effectively gather, store and present this data.
The value of big data is in the strategic insights it offers, which are uncovered by data scientists and analysts. However, it turns out that data engineers may be the missing element that makes company’s big data initiatives successful.
Brian Hills, head of data at Innovation Centre noted in an article for Data Economy, “One of the key learnings from the past few years is that success with data cannot be dependent on data scientists alone … Using only this approach within a business creates a cottage industry that limits ability to scale and generates a significant number of risks.”
He writes that data engineers also need to be part of the team, as they build the systems that enable data to be analyzed. There is growing demand for these professionals, with Stitch Data finding just 6,500 people with data engineer titles on LinkedIn and 6,600 job openings for data engineers in San Francisco alone.
Some 42 percent of data engineers have a background in software engineering, research by Stitch Data showed, while the top five data engineering skills are SQL, Java, Python, Hadoop and Linux.