The 8 Most In-Demand Big Data Roles

In today’s digital world there is no shortage of data. In fact, many times there seems to be too much. Companies are investing in cloud technologies, mobile technologies and social media. Combine that with everything else it takes to run an organization and you start to see how much data is being collected. Along with the rise of this data is an increase in demand for people who can collect, organize and make sense of it, according to recent data from Kforce, a staffing firm headquartered in Tampa, Florida.

The salaries listed here are from and are based on a typical IT professional working 40 hours a week.

With the eruption of data and the variety of data types that companies are seeking to take advantage of, there has been a significant increase in the need for professionals with the skills to acquire and integrate big data. ETL developers mainly work with different sources of data an organization may have and creates ways to extract data from sources, as well as, import it and modify it to fit the needs of the organization and then add it into a data warehouse.

“Given that the ETL software industry is rather mature, these positions are likely to have some of the longest tenures in the Big Data resource pool, and are often a mix of employees and contract resources,” says Greg Jones, CTO of Kforce.

Hadoop is a Java-based, open source framework that supports the processing of large data sets. According to Kforce, data within the framework of Hadoop and various technologies are in high demand — Hive, HBase, MapReduce, Pig and so on. This is due to the data volume demand, and the fact that the cost to process terabytes/petabytes with conventional business intelligence tools would be too cost prohibitive as well as take too long without massive distributed processing.

“Individuals with experience in the Hadoop framework are the most sought after resources in today’s big data landscape. These positions tend to be primarily contract resources as organizations mature their long term big data strategy,” says Greg Jones, CTO of Kforce.

Massive amounts of data can prove challenging to analyze. New types of visualization toolsets like Spotifre, Qlikview and Tableau allow for intuitive and speedy data probing. While these positions could fall close to a generic business intelligence developer category, Hadoop is really hot now and is a new breed of a specialized skill set, according to KForce.

“These skills are highly sought after in the short run as contract resources. As the supply of these resources catches up to the demand, and the toolsets mature, it is likely that the rates for these positions will moderate, and therefore more of these resources will converts to full time employee positions,” says Greg Jones, CTO of Kforce.

Previously referred to as data architects who were a part of IT, the data scientist is a new breed of technology professional able to tie their data organization techniques into business value propositions. They must also have great communication skills to explain data findings to both IT leadership as well as business leaders. These data scientists typically have their own sandbox in which to explore and examine an organization’s data and help drive innovation.

“Part analyst, part artist, a data scientist is somebody who is inquisitive, who can stare at data and spot trends. It’s almost like a Renaissance individual who really wants to learn and bring change to an organization,” says Anjul Bhambhri, vice president of big data products at IBM.

On-Line Analytical Processing developers are experts in the optimization of data organization to empower what Kforce calls, “slice and dice” analytics. This is the process of taking data from relational or nonstructured data sources and creating dimensional models — often referred to as “Star” and “Snowflake” Schemas, and then building the User Interface to access the data via high performance predefined queries.

“These individuals specialize in appliances such as Teradata, Neteeza and Exadata, according to Kforce. The core responsibilities associated with this role include data integration, administration and optimization of performance associated with these high end machines. These special appliances are used in an organization to provide Massive Parallel Processing (MPP), by using optimized memory, disk and data storage architectures specific to an analytics processing environment.” – Kforce’s Big Data Team

“Predictive analytics are used heavily in marketing organizations to predict consumer behavior and target product audiences,” according to Kforce.

This role can at times seem somewhat similar to the data scientist in the exploratory nature of what they do, examining many “what if? ” scenarios associated with an organizations data. These highly skilled IT workers are experts in building potential business scenarios, and utilizing assumptions based on historical data performance to test thresholds and predict future performance.

“Big Data has created a renewed interest in Data Mastery,” according to Kforce’s Big Data Team

To take full advantage and build an actionable plan using the company’s data takes a special skill set. Information architects must know how to define and document key elements and ensure that data is being organized and interpreted in the most impactful way. Master data management, business knowledge and data modeling are all key skills you’ll need if you’d like to occupy this role.