Big data is defined as a digital trace that is generated in the digital era. Hadoop is an open-source framework that allows the distributed processing of large data sets across the collection of computers along with simple programming models. Spark is also an open-source processing engine that provides users with different ways to store and make use of big data. This processing engine is built around speed, easy to use, and analytics.
As the world is getting increasingly digital and the value of big data and data analytics continues to grow in the upcoming years. The big data Hadoop/spark developer course teaches one the concept of the Hadoop framework and its formation in a cluster environment and prepares one for the introduction to big data with Spark and Hadoop. With the big data Hadoop/spark developer course, one will gain the big data framework using Hadoop and Spark, including HDFS, YARN, and MapReduce. This course focuses on Pig, Hive, and impala to process and even analyze large datasets stored in HDFS.
A Hadoop developer is in charge of the actual coding or programming of Hadoop applications. The role of the big data Hadoop developer is similar to that of a software developer. The main role of this is the same as the developer and is a part of the big data domain. In this article, let us have insights and gain knowledge about the job title.
Job responsibilities of Hadoop developer:
Hadoop developer serves many responsibilities, and the job responsibilities are dependent on the domain and sector in which this is applicable or not. The tasks which a Hadoop developer must perform include:
- Hadoop development and implementation
- Loading from disparate data sets
- Pre-processing using Hive and Pig
- Designing, building, installing, configuring, and supporting Hadoop.
- Translate complex functional and technical needs into detailed design
- Perform analysis of vast data stores and uncover insights
- Maintain security and data privacy
- Create scalable and high-performance web services for data tracking
- High-speed querying
- Manage and deploy HBase
- Put effort to build new Hadoop clusters
- Test prototypes and oversee handover for operational teams
- Propose best practices and standards
Big data Hadoop/ spark developer is a rewarding and lucrative career with huge growth opportunities. This job opportunity interests huge people, and interested candidates who wish to upskill with Hadoop and get on the Hadoop developer career path must choose this course for upskilling the career.
Skills required to become big data, Hadoop developer:
As of now, you are aware of the job responsibilities of a Hadoop developer. It is essential for one to have the right skill set for becoming one. Let us have a look at the right skillset which are necessary for the interstate candidate from different domains:
- Knowledge in Hadoop
- Good knowledge of back-end programming, especially Java, JS, Node.JS, and OOAD.
- Writing high performing, reliable and maintainable code
- Ability to write MapReduce jobs
- Have good knowledge of database structure, theories, principles, and practices
- Ability to write Pig Latin scripts
- Hands-on experience in HiveQL
- Become familiar with data loading tools such as flume, sqoop
- Knowledge of workflow, schedulers like oozie
- Analytical and problem-solving skills which are applied to the Big data domain
- Proven understanding of Hadoop, Hbase, Hive, Pig, and HBase.
- Good aptitude in multi-threading and concurrency concepts.
How to become a Hadoop developer?
To become a well known Hadoop developer, one must go through a different roadmap:
- Individuals must hold a strong grip on SQL basics, and the distributed system is mandatory.
- Create your own Hadoop projects in order to know in detail about the terminology of Hadoop
- Be comfortable with Java because Hadoop was developed with the use of Java.
General skills which are expected from Hadoop professionals:
- Capable of working with a huge volume of data for deriving business intelligence
- Knowledge for analyzing data, uncovering information, deriving insights, and proposing data-driven strategies
- Have knowledge of OOP languages such as Java, C++, and Python.
- Have an understanding of database theories, structure, categories, and practices
- Professionals must have knowledge of installing, configuring, maintaining, and securing Hadoop.
- Have an analytical mindset and the ability to learn and relearn different concepts.
Other few job roles and responsibilities according to the profile include:
Hadoop architect role: in this, one is entrusted with the responsibility of dictating the company will go in terms of big data Hadoop deployment. He is involved in planning, designing, strategizing the roadmap, and deciding how the company progresses. This professional must have hands-on experience in working with the Hadoop distribution platform. He must have end-to-end responsibility for the Hadoop life cycle in the company. He is the bridge between a data scientist, engineers, and company needs.
Hadoop administrator role: he is one of the prominent job profiles who are responsible for ensuring there is no roadblock to the smooth functioning of the Hadoop framework. This professional is responsible for managing and maintaining the Hadoop cluster for an uninterrupted job. Ensure the connectivity and network are always up and running. This professional regulates administration rights depending on the job profile of users.
Hadoop tester role: the main job of this tester has become critical since Hadoop networks are bigger and more complex. This poses a new problem when it comes to viability and security, and this works with no bugs. This professional is responsible for troubleshooting Hadoop applications and rectifying any issues. The duties include constructing and deploying the positive and negative test cases. Discover, document, and report bugs and performance issues, etc.
Big data is popular and considerable with a number of companies, and it does not remove the need for human insights. Big data career jobs are on the rise, and Hadoop is becoming a must-known technology in data architecture. Hadoop is a data warehouse and the new source of data within the enterprise. There is a grade on people who know enough about the guts of Hadoop to help companies take full advantage of the same.