Big Data // Hardware/Architectures
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6/24/2014
08:30 AM
Kevin Casey
Kevin Casey
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Hadoop Jobs: 9 Ways To Get Hired

IT recruiters share expert advice and creative tips for landing the Hadoop job or big data gig you want.
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You keep your skills sharp. You've built a fine professional network. You've buffed and shined your LinkedIn profile until it screams "HIRE ME!" And not a day goes by when you don't encounter another stat or sound bite telling you the demand for big data talent is white hot.

So why aren't you getting the big data job you want?

It could be any number of factors, including some that aren't visible or in your control whatsoever. But when it comes to the things you can control, are you doing everything possible to land the job that will supersize your big data career? Jobseekers in just about any career field know the agonizing purgatory that is The Hunt, not just for a job but the right job. There can be a whole lot of hair-pulling between the earliest stages of a search and an offer letter. Finding positions working with Hadoop and other emerging big data platforms is no exception.

We turned to several IT recruiters for help. What advice do they give IT pros -- whether newly minted graduates, well-credentialed veterans looking to make a career move, or people somewhere in between -- on landing not just an interview but an offer? Again, the idea is to find not just a job, but a great one.

You'll notice some themes here. First, strategic employers want well-rounded people for their big data initiatives. How's your Nietzschean philosophy these days? One senior recruiter told us that the best big data candidates he's encountered have a strong understanding of philosophy to pair with their technical backgrounds. Whether you're working with Hadoop clusters or Hive or Pig or YARN or any other technology, technical wizardry will take you only part of the way toward your goals. On the other hand, companies eagerly snap up people who can match that wizardry with the ability to identify and apply big data to real business challenges -- and translate the results for execs and stakeholders who don't dream in code.

Another theme: IT pros who take time to understand not just the data but the users or customers generating big chunks of that data will have a leg up on their peers. If you really want a particular position, don't just learn the ins and outs of the technologies you'll be using -- learn how and why you'd be using them for this particular company in this particular industry.

More than one of the recruiters we spoke with brought up the critical importance of being able to tell a story with data in terms of securing the job you want. Tom Hart, VP of marketing with the IT recruitment firm Eliassen Group, stresses the positive impact of pairing technology talent with the ability to communicate, narrate, and translate.

"If you really want to get a big data job, ideally, if you knew something about storing, retrieving and interpreting data, and something more about representing that information in a meaningful way with the use of dashboards and business intelligence tools, and you could convey your knowledge of both of these things in an interview with a hiring manager, your chances of employment would be materially enhanced," he says.

In other words, even in a jobseekers' labor market, tech chops will take you only to a certain point -- and that might not be exactly where you want to go unless you add storytelling prowess and other success factors. Read on for nine tips on landing the big data job you actually want.

What's worked for you in your own career? Share it with us in the comments.

(Image source: Intel Free Press)
 
Kevin Casey is a writer based in North Carolina who writes about technology for small and mid-size businesses. View Full Bio

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D. Henschen
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D. Henschen,
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6/25/2014 | 12:26:21 PM
Don't forget software-development and systems architecture skills
I've head lots of advice lately to focus on business requirements. Software development engineers and systems architects are good at this sort of thing because they're good at gathering and translating business requirements into working systems. In fact, these people may be in a better position to steer projects that DBA and relational database gurus who can point to data expertise but who may have a weaker link to working with the business and meeting business needs other than simple SLAs.
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