Hadoop Architect Job Description

Senior Hadoop Developer Jobs on Glassdoor.co

The growing importance of big data technologies like Hive, Pig, HBase, MapReduce, Zookeeper, and Hcatalog is driving demand for more jobs in the area of administration and developer jobs. Demand for high paid jobs in the area of Hadoop is growing at a rapid pace, and it is not just the tech companies that are offering it. There is increased demand for jobs in the area of administration and developer of the software.

Employers are looking for skilled talent in the form of Hadoop in greater numbers than ever before. Thousands of job openings for big data technologies can be found on the job portals such as Glassdoor.com. There are several openings for jobs in the area of Hadoop, like the one for the Hadoop Architects, the one for the Developers, the one for the Testers, and the one for the Administrators.

With large number of IT organizations using the technology to store and analyse data such as social media content, browser cookies, weblogs, click stream data to gain deeper insights about the preferences of their customer- Hadoop developer jobs and Hadoop admin jobs are growing in number. The job description for the position of senior Hadoop developer is included in the listing on glassdoor.co.in. Strong design and architecture skills are required of the developer.

The developer of the Hadoop software should have strong hands on experience and be able to architect big data end to end solutions. The job of a Hadoop developer includes understanding and working to come up with solutions to problems, design, architect and strong documentation skills. The link between the needs of the organization, the big data scientists and the big data engineers is defined by the description of the job of the Hadoop Architect.

A tester is supposed to find bugs in applications. A tester plays an important role in making sure the application is working as expected. A tester makes sure that the MapReduce jobs, Pig Latin script, and HiveQL script are working.

What is a Hadoop Developer?

A lot of people are confused about what a normal software developer is and what a Hadoop Developer is. The roles are the same, but the developer is in the Big Data domain. Let's discuss the points in detail about them.

The career of the Hadoop Developer is promising. Every industry requires a certain number of developers in the form ofhadoop. Skills are the main factors that can give you opportunities to lead your career in the right direction.

There are a wide range of responsibilities when discussing Job Responsibilities. If you have relevant skills on your resume, you can open a lot of opportunities for yourself. Skills required to become a proficient Hadoop developer are listed below.

Hadoop Architecture Design and Management

75% of Fortune 2000 companies will be running 1000 hadoop clusters by the end of 2020, according to Hortonworks founder. The toy elephant in the big data room is the most popular big data solution. Deployment and management challenges are still present in the implementation of Hadoop in production.

Apache Hadoop is a distributed computing big data framework that can be used to build a cluster of systems with storage capacity and local computing power. The Master Slave architecture is used for the transformation and analysis of large datasets. The skills required for a successful hadoop skillset include knowing the various components in the hadoop architecture, designing a hadoop cluster, performance tuning it and setting up the top chain responsible for data processing.

HDFS and MapReduce are used for data storage and processing. The master of both HDFS and Job Tracker are used for parallel processing of data using MapReduce. The other machines in the hadoop cluster are the slave nodes, which are used to store data and perform computations.

Every slave is connected to a Task Tracker daemon and a DataNode that syncs the processes with the Job Tracker and NameNode. The master or slave systems can be setup in the cloud or on-premise. A file on HDFS is split into multiple bocks and each is replicated within the cluster.

A block on HDFS is a blob of data that is in the underlying file system. The requirements can allow for a block to be extended up to a maximum of 256 MB. YARN stands for Yet Another Resource Negotiator.

Apache Map Reduce and Hadoop Cluster Resource Management

The master-slave architecture of Apache is that the master is responsible for assigning the task to various slave nodes, which are responsible for actual computation and store real data. Map reduce is the data processing layer of the platform and it distributes the task into small pieces and assigns those pieces to many machines. MapReduce uses a key-value pair to translate any type of data into a key-value pair and then processes it.

The data is moved to the processing unit rather than the other way around. The Resource Management level of the Hadoop Cluster is called YARN. It is used to perform job scheduling.

The idea of YARN is to divide the resource management and job scheduling into different processes and perform the operation. HDFS stands for a system. The core components of the Hadoop cluster are the file system and the database.

It can run on commodity hardware. HDFS is very similar to the existing file system. HDFS can store a lot of large data.

The Apache Hadoop Foundation: A Big Data Architecture for the Internet

The Apache Software Foundation, an NPO that builds open-source software, was aware in the early 2000s that new software tools were needed to help organizations exploit the increasing availability of Big Data. The group created an open-source tool called Apache Hadoop that would allow users to store and analyze data sets that were much larger than could be stored or managed on a single physical storage device. The basic architecture of the platform should remain stable despite the fact that it is easy to modify.

The Apache Hadoop Architecture has five essential building blocks that help to deliver the functions that organizations rely on for data management and processing capabilities. HDFS Federation is a way of creating and maintaining reliable and distributed data storage within the Hadoop architecture. HDFS has two parts: NameSpace and Block Storage.

Block Storage is involved with block handling and actual data storage, while NameSpace is responsible for file handling and storing. HDFS federation allows for horizontal scaling of NameNodes so that the cluster will still be available if a single NameNode fails. The technical complexity of the architecture is a major challenge.

Big Data Architecture Jobs: Cover Letters and Job Description

Big datarchitects are responsible for providing the framework that replicates the Big Data needs of a company using data, hardware and software, and cloud services, developers, and other IT infrastructure with the goal of aligning the IT assets of an organization with its business goals. Big data architects help identify existing data gaps, build new data pipelines, and provide automated solutions to deliver enriched data to applications that support the organization's operations. If you are writing a resume for a new job and you know you worked as a big datarchitect, you can use the work experience in the sample job description to make the work experience part of your resume.

The professional experience part of your resume is a chance to let the recruiters know that you have successfully performed the duties of a big datarchitect. If you want to move up in your career, you will need to acquire advanced skills and competence, which you can acquire by working as a big datarchitect. If you are hiring for a big datarchitect role, you need to inform prospective candidates of what the job entails, the duties and responsibilities they will be assigned, and how you will be compensated.

A Job Description for a Developer of Hadoop

The global community of users and contributors use the top-level project of Apache, called Hadoop. Apache is a programming framework used for large-scale storage and processing of Big Data in the distributed computing environment. Big Data is stored and processed using a tool called Hadoop.

Companies are using the technology to manage large amounts of data. To work on Hadoop, you need to know the Hadoop ecosystem. To perform the duties well, a developer needs to be familiar with the concept of Big Datand how to find value from the data.

A developer with a knowledge of playing with data, storing it, transforming it, managing it, and decoding it is the one who knows how to avoid it being destroyed. The skills of the developer open doors. If you want to get a high salary in the job of a Hadoop developer, you should have the skills listed on your resume.

There is no bar of salary for the person who can handle all the responsibilities of the job. The average salary for a developer of Hadoop is $108,500 per annum. The average salary for a developer of a Hadoop is more than the average salary for other open jobs.

Accredited Professional Certification for Big Data Hadoop Architecture

Big Data Hadoop architects are vital links between businesses and technology. They are responsible for planning and designing next-generation big-data systems and managing large-scale development and deployment of Hadoop applications. The average salary for a Hadoop architect is between $91,392 and $133,988 per year, and as much as $200,000 per year.

Any organization that wants to build a Big Data environment will need a Big Data Architect who can manage the complete lifecycle of a Hadoop solution, which includes requirement analysis, platform selection, design of technical architecture, design of application design and development, testing, and deployment of the proposed solution. If you want to learn the ins and outs of Big Data and Hadoop, you should get an accredited professional certification, which will back it up with authoritative validation. Apache Storm is designed for real-time event processing.

You need to master the fundamental concepts of Apache Storm to implement it effectively. An understanding of plan installation and configuration is required. The ability to query data in Apache Hadoop and skip the time-Consuming steps of loading and recognizing data is provided by Impala.

Software Developers in Hadoop Platform

You will learn different profiles in Big data to grow your career in the field of Big data, and you will have to have the skills and experience required for different profiles. High paid jobs in the area ofhadoop are being offered by IT companies and all types of companies are hiring high paid candidates There is a huge demand for jobs in the area of administration and developer of Hadoop.

There are many jobs for the job of a Hadoop Developer in Bangalore, and most of the time in India. The responsibilities of a developer in the Hadoop platform are to write programs that are in line with the system designs. The task of the developer is similar to the task of a software developer.

The System administrator job has similar responsibilities to the Hadoop Administration jobs. The admin roles and responsibilities of the Hadoop platform include setting up and maintaining clusters. Good knowledge of hardware systems and the architecture of the cloud is required by the administrator.

The Master-Slave Architecture

The master-slave architecture is used in the project. The basic idea of its design is to bring the computing to the data instead of the data to the computing. That makes sense.

It stores large files that are too large to fit one server. Map and Reduce operations further divide those and let each server in the node do the computing. When you first install it, it runs in a single node.

In production, you assign data to different machines in a cluster, meaning it would run on different machines. The cluster is a set of machines. A cluster can store a lot of data.

A database is not a tool for analyzing data. You cannot insert rows into tables or lines in the middle of files because there is no random access to data. You can Append and Cite files, but that is not often done.

Hadoop Clusters

The use of affordable commodity hardware allows for the efficient processing and storing of vast amounts of data. Thousands of low-cost dedicated server are working together to store and process data. A cluster of Master and Slave Nodes is called a Hadoop cluster.

HDFS and MapReduce can be linearly scaled out by adding additional nodes. There is always room for improvement in big data. The creation of new processing frameworks and APIs has been made possible by the introduction of YARN.

Big data continues to grow and the tools that can help with that are needed. A comprehensive Hadoop ecosystem includes projects that focus on search platforms, data streaming, user-friendly interface, programming languages, messaging, and security. The primary backup solution in early versions of Hadoop was the Secondary NameNode.

The Secondary NameNode downloads the current instance image and edits the logs from the NameNode. The fsimage can be retrieved and restored. MapReduce is a programming program that can process data.

Once a MapReduce job starts, the ResourceManager requires an Application Master to manage and monitor the job lifecycle. You need to make changes to the configuration files after you install and setup the distribution center. The parameters for the entire cluster are defined in the core-site.xml file.

The Art of Data Architecture

If you want to become a great datarchitect, you need to become a data engineer. The data architect is responsible for aligning all IT assets with the goals of the business in any data environment. Business owners will also use datarchitects to fill similar roles in their domain, just as a homeowner uses an architect to envision and communicate how all the pieces will ultimately come together.

A datarchitecture is a collection of resources that include data, software, hardware, networks, cloud services, developers, testers, and DBAs. It is the best part of being a big datarchitect. No one can stop you from becoming a big datarchitect.

Map Reduce Framework for Slave Data Nodes in Hadoop Cluster

Slave DataNodes are used for storing the data in a Hadoop cluster, the number of DataNodes can be from 1 to 500. The more DataNode the cluster has, the more data it can hold. The DataNode should have a large amount of storage capacity.

MapReduce works on a framework called YARN. Job scheduling and Resource Management are two operations that the YARN performs. The purpose of job schedular is to divide a big task into small jobs so that each job can be assigned to different slaves in ahadoop cluster and processing can be maximized.