A Hadoop Developer takes care of the coding and programming of Hadoop applications, in the context of Big Data. The position is similar to that of a Software Developer. Other occupations that are commonly associated with Hadoop Developer are Big Data Developer, Big Data Engineer, Hadoop Architect, Hadoop Engineer, Hadoop Lead Developer.
A good Hadoop Developer has a particular set of skills at their disposal, though businesses and organizations may place greater or lesser emphasis on any of the below-mentioned skills. Here is a list of skills that Hadoop Developers should know. But you don’t have to be a master in EVERY single one of them!
- Mandatory Knowledge of Hadoop and its appropriate components (e.g., HBase, Pig, Hive, Sqoop, Flume, Oozie, etc.)
- A good understanding of back-end programming, with an emphasis on Java, JS, Node.js, and OOAD
- A talent for writing code that is high-performing, reliable, and maintainable
- The ability to write MapReduce jobs and Pig Latin scripts
- Exhibit strong working knowledge of SQL, database structures, theories, principles, and practices.?
- Should have working experience in HiveQL.
- Possess excellent analytical and problem-solving skills, especially in the context of the Big Data domain.
- Have a useful aptitude in the concepts of multi-threading and concurrency.
Now that we know what kind of skills it takes to be a Hadoop Developer, what exactly do they do? A Hadoop Developer will be expected to:
- Take responsibility for the design, development, architecture, and documentation of all Hadoop applications
- Take charge of installing, configuring, and supporting Hadoop
- Manage Hadoop jobs by using a scheduler
- Write MapReduce coding for Hadoop clusters as well help to build new Hadoop clusters
- Convert complex techniques and functional requirements into the detailed designs
- Design web applications for querying data and swift data tracking, all to be conducted at higher speeds
- Propose the best practices and standards for the organization, then handover to the operations
- Perform software prototype testing and oversee the subsequent transfer to the operational team
- Pre-process data by using Pig and Hive
- Maintain company data security and privacy of Hadoop clusters
- Manage and deploy HBase
- Perform large data stores analyses and derive insights from them.
