Career in Hadoop

Hadoop is not a mere framework in the Big Data world. It has a wide ecosystem with an umbrella of related technologies. For the same reason, a career in Hadoop is promising. If you have a good understanding of Hadoop fundamentals, it will be a foundation for a great career in Hadoop. Predictions say that by 2025, 463 exabytes of data will be created each day globally which is equivalent to 212,765,957 DVDs per day! Each day 500 million tweets, 294 billion emails are sent, 4 petabytes of data are created on Facebook, 4 terabytes of data are created from each connected car, 65 billion messages are sent on WhatsApp, and many more. Thus, in 2020, every person is generating 1.7 megabytes in just a second. Can you imagine that every day we are generating 2.5 quintillion bytes of data? These Big Data without information is meaningless. Startups and Fortune 500 companies are embracing Big Data for achieving exponential growth. Organizations have now realized the benefits of Big Data analytics, which helped them in gaining business insights, which enhances their decision-making capabilities. It has been predicted that the Big Data market, by 2023, hits $103B. In 2020, the amount of global data sphere subject to data analysis will grow to 40 zettabytes, according to the predictions. The traditional databases are not capable enough to handle and analyze such a large volume of unstructured data. Companies are adopting Hadoop to analyze Big Data.

With the rise of the Big Data world, there arose a need for flawless systems that can process, parse, store, and retrieve such rising Big Data. The traditional databases are not capable enough to store the data generated in current times from heterogeneous sources. Also, they are not capable of fastly processing these vast amounts of data. Hadoop comes out like a light in the world of Big Data Analytics. In 2008, Apache Software Foundation developed Hadoop as an open-source software framework for storing and processing vast amounts of data. It has enormous processing power along with the capability to parallelly process and handle an unlimited number of tasks/jobs. Because of Hadoop’s unique features, such as its ability to store large data, its fast processing powers, fault tolerance, scalability, and cost-effectiveness, captivate Companies to adopt Hadoop. Also, Hadoop is not a single word; it is a complete ecosystem know as Hadoop Ecosystem that brings an additional point for Hadoop to be used by Organizations for crunching big data. Hadoop provides all that they need under one umbrella.

Education Required for Career in Hadoop

Like many emerging data technologies, Hadoop doesn’t demand any specific educational background as such. Around half of Hadoop, developers are from non-computer science backgrounds like Statistics or Physics. So it is clear that the background is not a hindrance to entering the world of Hadoop provided you are ready to learn fundamentals. There are good online courses covers Hadoop  – the one from eduCBA is the best example – master-apache-Hadoop

Further, if you want to move deeper into a specific area of Hadoop cluster management or data modelling in Hive materials on each specific topic available as online courses and textbooks, most of the time Hadoop clusters will be set up in a cloud vendor like AWS or Azure. So get familiar with any cloud vendor of your choice will help a lot. Hadoop service from AWS is called EMR.

The popular specialization includes :

·         Spark – Scalable in-memory data processing engine

·         HBase – No SQL Database on top of HDFS

·         Beam – Streaming first approach data processing

·         Pig – Data transformation(ETL) scripting

·         Hive – Data warehousing

·         Mahout, Spark MLlib – Scalable Machine Learning on Hadoop

·         Apache Drill – SQL engine on Hadoop

·         Flume, Sqoop – Data Ingesting Services

·         Solr & Lucene – Searching & Indexing

Career Path in Hadoop

As per Stack Overflow Survey 2017 results, Hadoop is leading in the most popular and most loved framework in Big Data space ( Survey Link). This is possible only because people from different IT perspective found Hadoop a potential career path and want to switch.

Whatever your current role is IT, there will be an easily adaptable switch to a career in the Hadoop world. Some popular examples –

·         Software Developer(Programmer): Hadoop Data Developer who deals with different Hadoop abstraction SDKs and derive value from data.

·         Data Analyst: So you are proficient in SQL.Huge opportunity in Hadoop to work on SQL engines like Hive or Impala

·         Business Analyst: Organisations trying to become more profitable using massively collected data and a business analyst role is crucial in this.

·         ETL Developer: If you are working as a traditional ETL developer, you can easily shift to Hadoop ETL using Spark tools.

·         Testers: There is a huge demand for testers in the Hadoop world. By understanding the fundamentals of Hadoop and data profiling, any testers can switch to this role.

·         BI/DW professions: Can easily switch to Hadoop Data architecting to Data modelling.

·         Senior IT professionals: With a deep understanding of the domain and existing challenges in the data world, a senior professional can become consultants by gaining knowledge of how Hadoop trying to solve these challenges.

There are generic roles like Data Engineers or Big Data Engineering, who is responsible for implementing solution mostly on top of Cloud vendors. By gaining knowledge of data components of the cloud provides, this will be a promising role.

Job Positions

Hadoop ecosystem offers a variety of career path.

·         MapReduce Developer: This basically a Java developer role who also understand how Hadoop systems work internally. There is an abstraction like Hive or Pig available still MapReduce jobs are necessary for high performing systems. MapReduce developers are the one who understands a system in and out and paid really high.

·         Hadoop Administrators: These are people responsible for keeping the Hadoop cluster healthy and performing. This may include typical Hadoop administrator tasks like regular system health checks, but most tasks are needed to understand Hadoop system architecture.

·         Devops: Deploy new system components and other development-related changes in Hadoop cluster. The responsibility of this role varies a lot and depends on the culture of an organization.

·         Data Developer: Data processing on top of Hadoop. This one of the most popular roles in the Hadoop ecosystem.People from SQL or analytics background best fit for these roles. Mostly work on a high-level abstraction of Hadoop like Hive or Pig.

·         Data security admin: Data is the most valuable assets, and securing it is most important. Security admins ensure industry-standard policies and best practices to protect data, understanding a system’s limitation.

·         Data Visualizer: Handle next-generation visualization tools which allow dynamic data slicing and aggregation with in-memory data caching

·         ETL Developer: Transform data for data quality improvement or as per business logic using Hadoop ecosystem tools. ETL process might be streaming or batch.

·         System Architect: Design high performing systems considering data availability and durability in a cost-effective manner. Depends heavily on Hardware provider.

·         Data Architect: Apart from traditional Logical/Physical design of data, a lot of things like column encoding, denormalization, partitioning design etc. will be a responsibility of data architect.

·         Recommended courses

·         Online XML and Java Training

·         Node.JS Courses

·         Silverlight Training Course

·         Ember.JS Program

Salary

An average salary of a Software developer in the US is $90,956 per year while the average salary of Hadoop developer is a way higher – $118,234 per year ( As per Indeed.com – indeed.com )