The Highest-Paid Big Data Skills

shutterstock_Maksim Kabakou

Yes, “Big Data” has become one of those buzzwords, along with “cloud,” that’s way overused these days. But it’s clear that employers want tech pros who can analyze massive datasets and deliver actionable intelligence: According to the most recent Dice Report, firms in several states consider data-analytics skills a critical resource, one that they’re more than happy to shell out big bucks to obtain.

Dice found that a full 24 percent of survey respondents in Seattle had Big Data skills—an unsurprising twist, considering the number of data-hungry firms (such as Amazon and Microsoft) that call the surrounding region home. Close behind it was Portland, with 22 percent, followed by Silicon Valley with 20 percent, Baltimore/Washington, D.C. (and its heavy contingent of federal agencies) with 19 percent, and Atlanta with 17 percent.

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Whether startups and tech giants on the West Coast or federal contractors in Washington, D.C., there’s clearly a demand for analytics abilities. But which of those abilities pay the best? Here’s Dice’s list of the top seven, by average annual salary:

Cassandra: $128,646
MapReduce: $127,315
Cloudera: $126,816
HBase: $126,369
Pig: $124,563
Flume: $123,186
Hadoop: $121,313

That doesn’t include perks or other incentives, of course. “Big Data” might be a buzzword… but it’s one that can prove lucrative for those with the aptitude for crunching it.

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Image: Maksim Kabakou/Shutterstock.com

5 Responses to “The Highest-Paid Big Data Skills”

  1. Prasad Joshi

    Big data and its tools are mainly hype.I expect this hype to run for one more year and then big bubble of big data is going to burst. Then people will start using RDBMS-Oracle,mySQL,Postgres..

  2. texas pete

    I agree with Prasad, almost completely. Many of the promises of “big data’ are falling short of the hype. for the following reasons:
    1.) The terms ‘Big Data’ and ‘Data Scientist’ are not well understood because they are not well defined. Most Engineers with a background in Math or Physics already have the required background in math & statistics at the undergraduate level to become Data Scientists. Computer science majors have a slight advantage when it comes to Algorithm design. T

    2.) Most products are based on the same open source projects hosted by Apache/Google/GNU. They all compete directly with middle-ware and database products from Oracle/IBM/SAP. These products already have large install bases, come with decent Math libraries and come have decent support.

    3.) What excites me about the latest generation of ‘Big Data’ tools lies in the field of Machine learning. Some really interesting work is now in the market in the form of Graph Databases, Neural Network based classifiers and elastic computing/adaptive networks. This is where open source has always excelled. Some companies are using machine learning in conjunction with traditional statistical tools. This seems to hold the best promise for big data and its elusive scientists.

    The problem I have with the article is that it seems to suggest that mastery of a single skill, such as Hadoop or Cassandra qualifies you to be a ‘Data Scientist’. The best ones I know are generalists. They come from Math, Physics, Chemistry and Cognitive Science backgrounds. They have developed skills in Networking, Distributed Systems and Software design.

  3. I’ve seen the hype of web – apps, RDBMS and Big Data is just marching like the rest. Give it time and Big Data will shine with security issues and such… Time is of the essences…!!