Big Data Hot Job: Data Engineer - InformationWeek

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Big Data Hot Job: Data Engineer
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pfretty
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pfretty,
User Rank: Ninja
9/12/2014 | 10:59:34 AM
Data culture
When it comes down to it, the more organizations embrace and leverage data to enhance operations and improve customer experiences (top two goals according to an IDG SAS survey), the more important it is to spread the focus and knowledge around to all the information users. I think there are benefits to having data scientists and data engineers, but where data is actually applied is far closer to the front line. These are the decision makers who need the skills and tools the most.

Peter Fretty

 
Gigi3
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Gigi3,
User Rank: Ninja
9/11/2014 | 1:07:12 AM
Re: Puffed-up title or truly different skills?
"I've seen some cases of people just upgrading their titles without upgrading their skills. But people who have truly graduated to data engineer can manage Hadoop clusters, handle data processing on the platform, and identify, move and, perhaps, cleanse and normalize subsets of data of interest for deeper analysis by the data scientists."

Doug, in career growth skill updation is more important than title. Titles imply only about responsibility and it can get changed at any instant. Moreover job can be executed through reporting subordinates. But skills matter and important as long as they are with industry.
Gigi3
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Gigi3,
User Rank: Ninja
9/11/2014 | 1:03:02 AM
Data Scientist
"It's been said many times that the key to a successful big data strategy is to hire a team of data-savvy individuals, each with a particular skill set, rather than trying to find a single data scientist adept at multiple disciplines, including computer science, mathematics, and domain expertise."

Jeff, that's a good option. So peoples with different skill set can work together for a single goal.
Laurianne
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Laurianne,
User Rank: Author
9/10/2014 | 4:24:59 PM
Re: Puffed-up title or truly different skills?
Self-upgrading of titles happens when a field is hot.
Doug Henschen
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Doug Henschen,
User Rank: Moderator
9/10/2014 | 12:43:38 PM
Puffed-up title or truly different skills?
In the legacy enterprise realm this data engineer/data scientist split would be akin to the data-management types (DBAs and ETL/data-integration professionals) versus the data analysts and analytics professionals (handling BI and data mining, respectively).

I've seen some cases of people just upgrading their titles without upgrading their skills. But people who have truly graduated to data engineer can manage Hadoop clusters, handle data processing on the platform, and identify, move and, perhaps, cleanse and normalize subsets of data of interest for deeper analysis by the data scientists. Data scientists, meanwhile, can write algos and develop data-driven applications from scratch whereas old-school data miners are more likely familiar with SAS, SPSS and perhaps R-based algorithms that can be called and tested in building models on supported workbenches or studios.

The old skills are still in demand, but the new skills are much rarer and sought after by pioneering data-driven organizations exploiting varied and high-scale data types not stored in old-school data warehouses. 


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