6 Tips for Landing a Job in the Big Data Industry

The information explosion is driving demand for qualified individuals in the booming Big Data industry. According to a recent study by the UK-based business analytics company SAS Institute, the number of employees that organizations will need to carry out Big Data tasks is expected to grow by more than 240 percent by 2017. What does that number mean for the U.S.?

As more and more companies turn to Big Data analytics platforms such as cloud-based Hadoop to collect, manage and mine mountains of rich data for competitive advantage, the demand for Big Data employees will dramatically outpace supply. According to a 2011 report published by McKinsey & Co., by 2018 the U.S. could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of Big Data to make effective decisions.

This huge talent gap represents a tremendous opportunity for those looking to pursue a career in the booming Big Data industry, provided they have the right qualifications. Based on a review of credible online sources that outline the qualifications Big Data employers are looking for in new hires, here are 6 tips for landing a job in the Big Data industry.

1. Have a Solid Skill Set

In a recent IEEE.org article, Dennis Shasha, a researcher in pattern recognition and database mining and associate director of NYU Wireless at New York State University, pointed out three important skills that are needed to be effective in handling Big Data. According to Shasha in the article, First is an understanding of databases and how they manage large amounts of data. Next is knowledge about machine learning and data mining, which allows inferences to be made from the data. Last comes statistics, so you can estimate the reliability of your conclusions.

In addition to those three skills Shasha also added that, Its important to understand the field in which the data is going to be used. This allows you to ask the right questions and design the right experiments to produce additional data.

2. Have a Curious Mind

Speaking of asking questions, being inquisitive by nature is an important trait, according to a recent InformationWeek article. In fact, a background in philosophy couldnt hurt, points out Jeff Remis, branch manager of the national IT practice at Addison Group. Having the background in Big Data helps you find the patterns hidden in the chaos, says Remis, but to understand the patterns takes someone with a trained philosophical mind. Philosophers are curious people who use logic and theory to tell a story with the data, which is what companies are looking for from analytics teams.”

3. Be Willing to Get Your Hands Dirty

While data science theorypresents a view of Big Data as tidy, unstructured Zettagytes of data are messy and complex. Thats why Mike Driscoll, CEO of Metamarkets, a San Francisco based data analytics company, says he prefers to hire candidates who arent afraid of what he calls the grimy work- the coal mining of the information age which is to extract, transform and load data. As quoted in a recent InformationWeek article Driscoll said that, the practical experience of building databases and handling “messy” data in the real world is a sign of someone who’s ready and willing to dive in and “learn the art” of data science.

4. Have a Hybrid Degree

In the aforementioned InformationWeek article, Mike Driscoll also indicated that a number of aspiring data scientists are pursuing hybrid degrees, such as a political science major with a minor in math. Driscoll feels that thats an excellent plan of action, being that, There are certain domains or areas of knowledge that are difficult to learn on your own and outside of a formal educational process—those domains are often the hard sciences.”

5. Leverage Related Skills

In a June 2014 article on InformationWeek, Adam Stillman, senior technical recruiter for Eliassen Group points out that both younger and veteran job applicants should not be, bashful about highlighting relevant skills that may be indicators of probable success in the Big Data world. In a tight labor market, Stillman suggests that prospective hires that lack hands-on Hadoop experience, but show that they, have Very Large Database (VLDB) and relational database management system (RDBMS) chops, could stand a better chance of being hired. The key, according to Stillman, is for the candidate to demonstrate strong theoretical knowledge in the area of Big Data.

6. Be Flexible

A number of web articles point out the importance of being flexible in searching for and obtaining a Big Data job. For the relatively inexperienced, this may mean taking a full-time job to get important practical experience with the Hadoop ecosystem from MapReduce to Oozie that can help lead to the dream job. The willingness to travel to a new area in order to obtain a position in Big Data is also important. Big Data is definitely hiring and the prospects for employment in the Big Data field are bright. Employing these tips and others can help Big Data candidates to find the best fit in an exciting industry that is rapidly growing and evolving.