Hadoop Developer Job Brief
We look forward to hiring a proficient and skilled Hadoop developer who will efficiently help build storage software. Besides, they must also have the capability of building big data infrastructure. The primary responsibility of the chosen candidate is to design, build, and maintain the Hadoop infrastructure.
Sometimes, the developers are also required to evaluate the existing data solutions. On the other hand, they must also be capable of developing documentation, writing scalable ETLs, and efficiently training staff. All Hadoop developers must possess in-depth knowledge of Hadoop API. Additionally, they must be able to manage projects and have high-level programming skills.
Hadoop Developer Responsibilities
Listed here are the job responsibilities of a Hadoop developer:
- Designing and coding the Hadoop applications for analyzing all data collections.
- Arranging meetings with the development team to assess the big data infrastructure of the company.
- Extracting data and isolating all the clusters of data.
- Creating compelling data processing frameworks.
- Troubleshooting significant application bugs.
- Testing scripts and analyzing the results closely.
- Creating efficient data tracking programs.
- Maintaining complete security of company data.
- Providing hands-on training to all the staff regarding the ways of using applications.
- Producing the documentation of Hadoop development.
- Proposing the best standards or practices of Hadoop.
- Efficiently translate complex technical and functional requirements into a deliberately detailed design.
- Developing and implementing Hadoop.
- Pre-processing data using Pig and Hive.
- Loading Hadoop data from disparate data sets.
- Performing analysis of vast data stores while uncovering insights.
Hadoop Developer Requirements
Listed here are the job requirements of a Hadoop developer:
- Hands-on experience as a big data engineer or a Hadoop developer.
- A bachelor’s degree in computer science, software engineering, or any other relevant field.
- In-depth knowledge of HBase, Hive, and Pig.
- Extensive and advanced knowledge of the Hadoop ecosystem along with its components.
- Greater familiarity with Pig Latin Scripts and MapReduce.
- High-level problem-solving and analytical skills.
- Extensive familiarity with data loading tools, including Flume and Sqoop.
- Magnificent communication and management skills.
- Hands-on experience in HiveQL.
- Excellently proven understanding and knowledge of schedulers/workflow like Oozie.
- Extensive knowledge of database structures, principles, theories, and practices.
- The ability to write high-performance, maintainable and reliable codes.