Shulou(Shulou.com)06/03 Report--

Why do big data engineers earn more than Java programmers?

Codo big data development course mainly trains Java engineers and development engineers, including Java and big data parts.

As a mainstream programming development language and workplace skills, Java has been recognized by more and more fresh graduates and newcomers to the workplace. More and more people are learning Java programming technology through various training institutions or online courses, constantly increasing the supply of Java programmers.

In the eyes of recent college students, rookies and non-IT people, learning Java technology is undoubtedly a good choice for Java programmers, which at least solves their top priority-survival problem to some extent.

However, for Java programmers who have been in the profession for 2-3 years, the survival problem has been alleviated and solved, and they are more concerned about, "can this path continue?" , "can the salary continue to increase by more than 30% next year?"

Here I still want to recommend the big data Learning Exchange Group I built myself: 529867072, all of them are developed by big data. If you are studying big data, the editor welcomes you to join us. Everyone is a software development party. Irregularly share practical information (only related to big data software development), including the latest big data advanced materials and advanced development tutorials sorted out by myself. Welcome to join us if you want to go deep into big data.

For programmers, technology is developing all the time, and it is necessary to keep pace with the times. Big data has a huge talent gap, and there is an opportunity for transformation. If you can seize this rare opportunity to become a big data engineer to take you further (competitiveness, money, etc.), why not do it?

Big data is engaged in open source work, more inclined to "research and development", can re-arouse programmers' enthusiasm for R & D programs, and have a new pursuit in their career, which means that big data will become a job worthy of programmers' long-term struggle and continuous breakthrough; secondly, as big data belongs to an emerging field, there is a relatively lack of professionals, and high-end talents are the object of enterprise competition. It is easy for salary to rise and there is great potential for career development.

It is also good to do Java, but at present big data is a trend, enterprises with a little more strength are on the big data project, and Hadoop itself is developed by Java, and Hadoop engineers are generally higher than pure Java development by more than 3k, so there are a lot of Java people who are turning to hadoop big data.

Big data is related to 10% of domestic IT, communications and industry recruitment, and the proportion is still on the rise. The huge talent gap has directly led enterprises to hire big data talents with high salaries:

There are already many people who work as Java, and many people can hardly earn more than 20, 000 a month for 4 to 5 years, and few can earn more than 25000. But many people in Hadoop earn more than 20, 000 after only one year of experience. Therefore, many people who are still well paid now also come to talk about Taiwan Hadoop, mainly to consider the issue of the ceiling of future development.

If Java works for 5-6 years to a management position, the salary can basically reach 20-25000. But 25000 is basically the ceiling of Java technicians, and very few people can do it unless they are architects or low-level developers. But the salary of more than 20, 000 Hadoop is only mediocre, and there is still a lot of room for development, so many experienced Java birds are turning to this area.

Old age is a big problem for technical people. Java engineers are all over the street. When they are old, their wages are good, but they can't keep up with young people, they can't work overtime, and they can't travel for a long time even if they have a home.

The age impact of Hadoop is relatively small, because doing big data is not a simple programming, and the weight of programming is less than 1Universe 6. Very often, you need to analyze and solve problems from server, storage, computing, operation and maintenance and other aspects. The older you are, the more experienced you are, and the more popular you are. Big data Learning Exchange Group: 529867072

What abilities does big data engineer need to have?

(1) background related to mathematics and statistics

(2) computer coding ability

(3) knowledge of specific application areas or industries.

Big data engineer's role is very important, can not be separated from the market, because big data can only be combined with specific areas of application to generate value.

Therefore, experience in one or more vertical industries can accumulate knowledge of the industry for candidates, which is of great help to become big data engineer later, so this is also a more convincing addition when applying for this position.

Big data has many related skills, which can be divided into five categories according to the data itself: data acquisition, data processing, data analysis, data storage and data mining.

Data acquisition: log collection Scribe, Flume, crawler, etc.

Data processing: streaming computing storm, spark streaming, Hadoop, message queuing related such as Kafka, etc.

Data analysis: HIVE, SPARK, basic algorithm, data structure, etc.

Data storage: HDFS, etc.

Data mining: machine learning related algorithms, clustering, time series, recommendation system, regression analysis, text mining, Bayesian classification, neural network and so on.

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