Big Data/ Hadoop Admin

**Detailed Job Description: Big Data Admin/DevOps**

**Key Objective**:
As a Big Data Admin/DevOps professional, your primary role will be to manage the end-to-end Hadoop infrastructure, ensuring its efficiency, security, and stability for large-scale data processing and analysis.

**Primary Responsibilities**:
Maintain End-to-End Hadoop Infrastructure:
l You will oversee the entire Hadoop ecosystem, ensuring that all components like HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator), HBase, Hive, Spark, and other related tools are functioning seamlessly.

l You'll be responsible for managing the cluster, ensuring its performance, reliability, and scalability as data processing needs grow.

**Roles and Responsibilities**:
**Minimum 6 Years of Experience in Hadoop Environments**:
l You must have a solid background working with Hadoop, particularly in administrative or development capacities, over a significant period to manage large, complex systems.

l This experience ensures a deep understanding of the Hadoop ecosystem, including best practices for deployment, optimization, and troubleshooting.

**Advanced Knowledge of the Hadoop Ecosystem and Its Components**:
l The role demands comprehensive knowledge of Hadoop components like HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, and others. You should understand how these components integrate and function within the system.

l Your expertise should include tuning, scaling, and optimizing these components to meet business needs.

**Installing, Configuring, and Supporting Hadoop**:
l You will be tasked with the complete lifecycle of Hadoop components, from installation to configuration and ongoing support.

l This includes setting up cluster nodes, ensuring proper networking, configuring resource management, and managing storage.

**Real-Time Troubleshooting of Hadoop Infrastructure**:
l You will need practical, hands-on experience in resolving infrastructure issues as they arise in real
- time.

l This could involve fixing connectivity issues, optimizing slow queries, or troubleshooting node failures in a multi-node environment.

**Understanding and Implementing Hadoop Security Mechanisms**:
l Hadoop security can be complex, with elements like Kerberos authentication, encryption of data at rest and in transit, and role-based access control (RBAC).

l You should have the ability to configure and implement these security protocols to protect the integrity and confidentiality of data.

**Ensuring the Chosen Hadoop Solution is Deployed Without Hindrance**:
l You will ensure that the deployment of Hadoop-based solutions, such as a data processing pipeline or a data analytics platform, proceeds smoothly without technical or operational roadblocks.

l This requires strong project management skills, in addition to technical knowledge.

**Hands-On Experience with GIT and CI/CD**:
l Experience with GIT version control is essential for managing codebases used in Hadoop and Spark jobs.

l CI/CD (Continuous Integration/Continuous Deployment) pipelines will be required to automate deployment and testing processes. Knowledge of tools like Jenkins, Docker, or Kubernetes will also be helpful.

**System Test for Big Data Admin/DevOps**:
This system test is designed to assess your hands-on technical abilities in a real-world scenario:
**Install and Configure a Hadoop Cluster and Spark Cluster**:
l You will be required to install and configure a Hadoop cluster (for distributed storage and processing) and a Spark cluster (for fast, in-memory processing).

l This involves setting up nodes, configuring resource allocation, and ensuring communication between nodes.

**Install and Configure Hadoop Components**:
l **HDFS (Hadoop Distributed File System)**:Manage distributed storage for large datasets.

l **YARN (Resource Manager)**:Allocate system resources to different tasks.

l **Hive Metastore with RDBMS**:Hive is used for querying and managing large datasets. You’ll configure it with an RDBMS (like MySQL or PostgreSQL) as its metastore.

l **Sqoop**:Integrate Sqoop to transfer data between Hadoop and traditional databases (e.g., importing/exporting data).

l **Kafka Cluster**:Set up Kafka, which is essential for real-time data ingestion into the Hadoop ecosystem.

**Import Data to HDFS**:
l After configuring the clusters and components, you’ll import data into HDFS. This is a critical task as you’ll manage and ensure the integrity and flow of large datasets into the Hadoop cluster for processing.

**Key Skills and Tools Needed**:

- Hadoop ecosystem knowledge (HDFS, YARN, Hive, HBase, Pig, etc.)
- Strong hands-on experience with Hadoop/Spark cluster configuration and administration.
- GIT version control for source code management.
- CI/CD pipeline management for smooth and automated deployments.
- Security implementation expertise (Kerberos, encryption, etc.).
- Experience with data ingestion tools like Kafka and Sqoop.

This role combines deep tec