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Rishabh
Hadoop Developer
Rishabh is a software engineer having 7+ years of experience developing web applications that manage and track data at a very high speed.
Expert in
Node.js
Hadoop
CSS
HTML
Experience
10 Years
Availability
Full Time
Mahesh
Hadoop Developers
Mahesh is a software engineer having 3+ years of experience in developing Hadoop applications and turning functional requirements into extensive designs and architecture.
Expert in
HBase
Hadoop
CSS
HTML
Experience
10 Years
Availability
Full Time
John
Hadoop Developer
John is a software engineer having 10+ years of experience in documenting, designing, and building robust Hadoop applications and testing various software prototypes.
Expert in
YARN
Hadoop
CSS
HTML
Experience
10 Years
Availability
Full Time
Hire top talented Hadoop developers with UltraGenius
Hadoop is widely used software for storing and processing large amount of data efficiently. Hadoop implements the mechanism of parallel processing by dividing the big task into several small tasks ensuring each tasks is operated by multiple slaves in the cluster.
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Want to hire Hadoop developers on your own? Here are the skills you must look for while hiring a Hadoop developer
Hiring Hadoop developers might be an intricate task for you if you are a non-technical manager. Hadoop is a prominent open source framework for handling a massive amount of data and its computation. Hadoop provides clustering multiple computers to parallely analyze datasets instead of using a single computer to store and process a large amount of data. But, hiring the top talented Hadoop developers among thousands of developers is a challenging task for anyone. So, Ultragenius is here to assist you while recruiting the top talented Hadoop developers on your own. Ultragenius understands your job requirements and gets you only the top developers who have sufficient experience working with Hadoop.
The following skills you must look for while hiring a Hadoop developer –
Solid understnading of HTML and CSS
HTML (Hypertext Markup Language) and CSS (Cascading Style Sheets) are the two must knowing technologies for a Hadoop developer. You must hire such a developer who have worked with these technologies in-depth. Knowledge of Flexbox and CSS Grid, in addition to Bootstrap, Semantic and Structural Styling, and Foundation is a must to a Hadoop developer. Along with this, the developer should be well-versed in Javascript libraries especially jQuery and CSS grid systems.
Familiarity with Javascript fundamentals especially with ES6
Javascript is most widely used language in developing dynamic web applications and helps a developer integrate back-end with the front-end easily. The Hadoop developer must be clear with the fundamental concepts of Javascript language. ECMAScript 6 (or ES6) is the current version of ECMAScript and is widely used by developers up to a large extent. The Hadoop developers must be familiar with these ES6 skills –
- Arrow functions
- Blocked scope constructors let and const
- Advanced object literals
- Template literals
- Multi-line strings
- Modules
- Module loaders
- Binary and octal literals
- Reflect API
- Proxies
- Classes
- Destructuring assignment
Knowledge of Hadoop Distributed File System
Hadoop Distributed File System (HDFS) is a storage component that manages massive amounts of data on a commodity hardware. Here are some characteristics of HDFS :
- HDFS recovers faster from hardware failures.
- HDFS is most suitable for streaming access to large datasets.
- HDFS supplies a strong bandwidth handling thousands of nodes in a single cluster.
- HDFS is compatible with various platforms and operating systems.
Check the Hadoop developers knowledge about NameNodes, DataNodes, Hadoop Daemons, Hadoop Architecture, etc.
In-depth knowledge of Hadoop architecture
The Hadoop developer must strongly know about Hadoop ecosystem, components, and interfaces. The Hadoop Architecture comprises of four components –
- MapReduce – MapReduce enables parallel distributed processing which makes Hadoop to perform fast.
- HDFS – Hadoop Distributed File System (HDFS) stores the data in a large block rather than storing the data in small blocks. HDFS is designed on the distributed software concept.
- YARN – Yet Another Resource Negotiator (YARN) performs tasks of Job Scheduling and Resource Management. The job scheduler divides the large processes into smaller ones and ensures that each process gets assigned to multiple slaves in a Hadoop cluster thus enabling parallel processing.
- Hadoop Common – Hadoop Common is the java library that is needed for the components present in the Hadoop cluster and is used by MapReduce, YARN, and HDFS for running the cluster.
Experienced in working with code versioning tools like Git, SVN, TFS
Hadoop Developers must possess excellent knowledge of version control systems, like Git, SVN, TFS, and Mercurial. Mostly, developers use Git for their work. It is the version control system that helps the team in collaborating and organizing your code, maintain the frequent changes that occur in the code. Git helps in reviewing the old codes and compares them with the newly updated code, pulling the code from their repository, and managing the commit history.
Check if the Hadoop developer knows about add, push, pull, and commit commands, branching, and merging as it allows developers to work independently on the code.
Excellent grasping on Hadoop Hive, Hbase, and Pig
Big data Hadoop developer must know about Hive, Pig, and HBase. Pig Hadoop is used for handling semi-structured data. HBase is used for handling unstructured data. Hive is designed to work quickly for large amounts of data.
- Hive provides SQL-like query engine that allows users to read, write, and manage data. Hadoop Hive functions on the server-side of any cluster.
- HBase is non relational database management system that is used to store and process large amounts of data. Check if the Hadoop developer knows about HMaster, Region server, and Zoom keeper.
- Pig Hadoop is a very advanced tool that operates on the client-side of any cluster. Pig is well known for powerful transformation and enhanced data processing.
Experience working with HiveQL
Hadoop Hive provides a SQL-like query language for querying and handling massive datasets known as Hive-QL. Hive provides the facility to write the custom MapReduce framework that can perform complex data analysis. Hive DDL commands are quite similar to SQL DDL commands – CREATE, DELETE, ALTER, DESCRIBE, SHOW, and TRUNCATE.
Knowledge of Front-end frameworks and libraries
Hadoop developer must know about front end technologies and frameworks particularly React.js or Angular.js. These front-end frameworks are greatly required in today’s market. React is popular for its faster development of Single Page Applications while Angular uses interpolation, dependency injection, and eliminates coding mistakes by using the strongly typed Typescript that resolves many challenges faced by the developers.
Extensive knowledge of Java and Object Oriented Programming Concepts
Hadoop framework is written in Java. Java is used for storing, handling, and processing massive amount of data. Check if the Hadoop developer knows the fundamental concepts of Java like Multi-Threading, Exception Handling, Collections, String Handling, OOPS concepts (Data Encapsulation, Abstraction, Inheritance, and Polymorphism), and Generics.
Knowledge of MapReduce programming model
Traditional data programming model works by having a centralized server to store and perform calculations on data. However, it is not suitable for processing large amount of data. Therefore, MapReduce was introduced to solve handling big datasets. MapReduce is a programming model which divides the large data set into multiple smaller data sets and assigns them to multiple servers. Map splits and maps the data with key-value pair while Reduce sorts the intermediate data and reduces it into smaller data units.
Knowledge of backend programming with Node.js
The Hadoop developers must have experience working with Node.js run-time environment. Many Hadoop application require integration with Node.js. Moreover, the developers must be aware of the existing packages which help in Big Data development like mesos, dockerode, hipache, overcast, spm-agent-nodejs, and dyndns.
Hands-on knowledge of Linux commands
Linux provides a variety of tools to operate and compute the data sets. Data processing and computing is much faster than Windows. Ubuntu is widely used operating system by big data professionals. Check if the Hadoop developers knows these commands – cd, cd dir, ls, ls al, appendToFile, cat, checksum, chown, chgrp, chmod, copyToLocal, copyFromLocal, count, df, du, get, find, expunge, help, mkdir, ls, lsr, moveFromLocal, mv, put, rm, rmdir, rmr, stat, and tail.
Firm understanding of data loading tools like Flume
Flume is a robust, reliable, flexible, and configurable tool used for collecting, aggregating, and transferring massive amount of unstructured data from various data sources to Hadoop Distributed File System (HDFS). Main components include Flume Events, Flume Agents, Source, Channel, and Sink and additional components are Interceptors, Channel Selectors, and Sink Processors.
Proficient writing reliable, manageable, high-performance code
You must hire the Hadoop developers based on the ability to write proficient, high-quality, reliable, and high-performance code for big data applications.
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Connect with the top 1% Hadoop developers of the world at the lowest prices
Hadoop is widely used open source framework that uses distributed storage for storing large datasets ranging from gigabytes to petabytes and processing big data using the MapReduce programming model. Hadoop provides a great flexibility computing massive amount of data. But recruiting the best Hadoop developers is not an easy task when a large no. of Hadoop developers are competing to grab the job opportunities.
Top Interview Questions to ask while hiring the best Hadoop developer
Frequently Asked Questions
Ultragenius is one of the leading platforms for hiring remote talent and connecting developer and part-time developers with Silicon Valley businesses. We focus on finding the best talents who will perform extremely well and will be easily integrated into your teams. We filter out only the top 1% most skilled developers among the 20K+ developers who have applied on our platform. Candidates have to prove their self-reported experience by giving Ultragenius’ s skill tests.
Ultragenius first tests the developer’s skill set by conducting a two and half hour hiring test. Our hiring test judges a candidate on all aspects like aptitude, case study analysis, verbal and reasoning, coding questions based on data structures and algorithms, software engineering, system design, and more. Then, there is another round for the candidates who are selected from this round called “Higher-level Assessment Skill Test”, which is a video round that deeply analyzes developers’ major skills and asks questions about the projects they have worked upon.
Fill up the form which is on every hiring developers’ page and we will inform you once we select the top 1% Hadoop developers matching your job requirements. After analyzing the candidates based on their resumes and two assessment tests, we provide you the feedback quickly. And if the developers selected by our team are fit for your job role, then we also provide the onboarding.
Ultragenius offers you only the most skilled developers who are top 1% among the 20K+ developers who have applied on our platform. After a rigorous selection and testing process, we sort out only the top candidates for you. You can check out Ultragenius’ s selection process for hiring Hadoop developers on https://www.ultragenius.club/hire-hadoop-freelancer.
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