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.
• Data change agents: People who drive changes in internal operations and processes based on data analytics. They may come from a Six Sigma background, but they also need the communication skills to translate jargon into terms others can understand.
• Data engineers/operators: The designers, builders and managers of the big data infrastructure. They develop the architecture that helps analyze and process data in the way the business needs it. And they make sure those systems are performing smoothly.
"The people who do the best are those that have an intense curiosity," says D.J. Patil, data scientist in residence at Greylock Partners. Patil probably knows what he's talking about: Forbes magazine credits him and Cloudera founder Jeff Hammerbacher with coining the term data scientist. And earlier in his career, Patil helped develop the data science team and strategy at LinkedIn.
- Tam Harbert
Sign up for CIO Asia eNewsletters.