Big data came into existence and opened the door to a broad spectrum of job opportunities awaiting skilled and suitable candidates. One of the most sought-after job in the big data market is Hadoop developer whose salary ranges from $92,000 to $105,000 per year. Hadoop is considered to be the mother of all the big data technologies which makes it an efficient platform to take-off your career in this domain.
What is Hadoop Developer all about?
There are many job roles that work simultaneously on a Hadoop platform like Hadoop administrator, Hadoop ETL developer, Hadoop architect, Hadoop analyst, Hadoop tester, etc., but one of the coveted profiles is the Hadoop developer. A Hadoop developer is responsible for coding of applications. These codes are developed for storing, managing and analyzing the big data on the cluster.
A Hadoop developer can be understood the counterpart of a software developer working in Big data platform. Fundamentally Hadoop developers are responsible for:
- Writing jobs in MapReduce
- Programming in Java, JS, etc.
- Writing scripts in Pig and Hive
- Loading and extracting data from HDFS
- Reviewing the Hadoop log files
- Coordinating and scheduling the jobs across the Hadoop cluster, etc.
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Clearly a Hadoop developer is not only responsible for creating codes but a lot of things additionally that make him an all-rounder performing multiple tasks at once.
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Skill-set required to become a Hadoop Developer
Hadoop does not work alone but many of the additional software packages jointly make the Hadoop architecture like Hive, Ambari, HBase, Pig, Oozie, Flume, etc. Therefore a Hadoop developer should have a good knowledge about these technologies. However an aspirant should always know the distinction between a ‘must-have skills’ and ‘good-to-have skills’. Though a complete knowledge is beneficial but a smart work on it will definitely give you an upper hand.
|Must-have Skills||Good-to-have Skills|
- Hadoop Framework
- ETL tools (Informatica, Talend, Pentaho)
- Visualization tools (Tableau, Qlikview, etc)
- Gateway nodes and edge nodes
- Cloud computing
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How should you prepare yourself for a Hadoop Developer interview?
Cracking any interview needs a lot of preparation on various aspects. Similarly a Hadoop developer should pay special attention to several technologies which are crucial to successfully crack the interview.
One of those technologies is MapReduce which is a processing technique deployed on distributed environment. MapReduce performs some of the crucial jobs by splitting those in multiple parallel tasks to be processed in real-time which is why interviewers are keen on asking complex questions on MapReduce. A Hadoop developer should be proficient in writing MapReduce jobs.
While Java stands as the most preferred programming language for developing application codes, there are other programming languages like JS, Node.js, OOAD which make you stand out from the crowd. Another technology which is extremely important for any Hadoop professional is HDFS. HDFS is a distributed file system for storing large files and streaming the data to the applications.
Hadoop is just not all about its core components, but there are other technologies that seem small but play a pivotal role in processing distributed data on the cluster. Some of such technologies are Pig, Hive, Sqoop and Flume. These technologies make the data processing and managing tasks easier on Hadoop cluster. While mastering HiveQL will give you an added advantage, hand-on experience on writing scripts in Pig and ingesting data using sqoop and flume will certainly add value to your resume.
Find what top-notch companies ask in the interview for Hadoop developer here!
Three essential interview suggestions
Though gaining knowledge is the foremost activity a candidate should focus on, there are certain things that an individual should work on before appearing for a Hadoop developer interview. These are-
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- Practical experience rather than mere theoretical knowledge- An individual aspiring to become a Hadoop developer should always emphasise on gaining practical knowledge in related technologies rather than merely concentrating on learning theories. Though theoretical knowledge is significant but working on technologies give a different exposure to the candidates making them outperform others.
- Good communication skill- Knowledge goes in vain if not communicated properly. Since Hadoop developers work closely with architects, engineers and analysts, effective communication plays an important role in fulfilling the job responsibilities.
- Domain knowledge- Hadoop is one of the many technologies used in big data world. The candidate should be knowing the competitors of Hadoop as well as many other related technologies along with their basic functionalities. This will help him better support his answers on comparative grounds.
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