"There's a nuanced leap there when you move into this big data environment," Yu says. "You're really looking at the optimal configuration of taking these massive processing jobs and figuring how do you distribute this load on servers that are much less monolithic and much more distributed."
In addition to database knowledge, Yu notes that strong backgrounds in computer science, algorithms and OSes are helpful bases to a BrightEdge data science career.
"If they have a good foundation in that, then you pair that up with a [training] program that allows them to understand how to translate into this new architecture," he says. This buddy system, which matches workers who have worked on the big data stack with people who are learning the system, leads to knowledge sharing, he said.
This method also helps people new to extreme data crunching learn which data processing jobs call for big data technology and when to use traditional relational databases, Yu says.
"With big data, one of the advantages is the scale of what you can do," he explains. "But it also means you don't have the same speed of development from having the really simple, flexible standardized SQL language that you can apply to the data set. There are tradeoffs that you're making. It's important for the technology staff to have a good appreciation of that."
DataXu, a Boston company that offers a product for managing online advertising campaigns, also takes a team approach to filling data science jobs, says CTO Bill Simmons. Big data workers there have strong math and coding skills and some business savvy, he says.
People who excel in one area, are strong at a second and have a grasp of the third allow the company to form teams based on different strengths.
Possessing "two out of the three is what you need to get the job done," he says, adding that finding people who have a strong background in one of those areas is fairly easy. Standouts in all three skills are harder to come by. "I would be delighted finding someone who is a star in all three areas."
Employers also seek workers whose software skills and data backgrounds match their work environments.
Companies select database software that can handle their data sets, which can be complex, says Rob Byron, a principal consultant in the information technology division of staffing firm Winter, Wyman. Employees, for their part, prefer to stick with the software they know.
"The general outlook is if we have a SQL server data warehouse I'm looking for Microsoft [skills]. Oracle people need not apply. And vice versa. And quite frankly a lot of candidates don't want to learn new skills," he says.
Given the amount of data companies are dealing with, they only want candidates who have handled that volume, says Modis' Kelley. A person's data experience, not the industry they're in, is what matters to employers, she notes.
"Data is data," she says. "Industry vertical really isn't going to be the key driver. Its going to be what did you do with the data, how large of an environment was it."