Wanted: Relentless, scientific temperament
Until recently, creativity, curiosity and communications skills haven't typically been emphasized in IT departments, which may be why many employers aren't looking to their IT operations staffs to find people to spearhead big data projects.
The IIA sees data science as resting on three legs: technological (IT, systems, hardware and software), quantitative (statistics, math, modeling and algorithms) and business (domain knowledge), according to Phillips. "The professionals we see who are successful come from the quantitative side," he says. "They know about the technology, but they aren't running the technology. They rely on IT to give them the tools."
Big data also demands a scientific temperament, says Wills. "When we talk about data science, it's really an experiment-driven process," he explains. "You're usually trying lots of different things, and you have to be OK with failure in a pretty big way." Wills goes on to say that there's a "certain kind of relentlessness you need in the personality of someone who does this kind of work."
Big data professionals also have to be intellectually flexible enough to quickly change their assumptions and approaches to problems, says Brian Hopkins, an analyst at Forrester Research. "You can't limit yourself to one schema but [need to be comfortable] operating in an environment with multiple schemas or even no schemas," he says.
That tends to be a different approach than most IT people are used to. "IT people coming out of a strong enterprise IT shop are going to perhaps be constrained a little bit in their ability to do things quickly and move fast and be agile," Hopkins says.
But once hiring managers find the right type of person, they're usually willing to retrain that person to fill a big data role. For example, Patil used to work at LinkedIn, where, he says, "we largely trained ourselves, because so much of this is open source." He thinks the same thing can happen at most companies. "You can make these people" -- if they have the right personality, he says.
IT workers who are flexible, willing to learn new tools and have a bit of an artist somewhere within can move into data architecture or even data visualization, says Sacheti.
In short, big data carries big potential for IT pros who would relish an opportunity to show their creativity.
Big data job titles and skills
Without conventional titles, or even standard qualifications, it's hard to know what makes someone suitable for a big data job. This listing, based on interviews with big data experts and recruiters, attempts to match up some of the most common titles with the skills required.
• Data scientists: The top dogs in big data. This role is probably closest to what a 2011 McKinsey report calls "deep analytical talent." Some companies are creating high-level management positions for data scientists. Many of these people have backgrounds in math or traditional statistics. Some have experience or degrees in artificial intelligence, natural language processing or data management.
• Data architects: Programmers who are good at working with messy data, disparate types of data, undefined data and lots of ambiguity. They may be people with traditional programming or business intelligence backgrounds, and they're often familiar with statistics. They need the creativity and persistence to be able to harness data in new ways to create new insights.
• Data visualizers: Technologists who translate analytics into information a business can use. They harness the data and put it in context, in layman's language, exploring what the data means and how it will impact the company. They need to be able to understand and communicate with all parts of the business, including C-level executives.