Minimum 3-5 Years of Experience in Hadoop Environments:
You must have a solid background working with Hadoop, particularly in administrative or development capacities, over a significant period to manage large, complex systems.
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:
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.
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:
HDFS (Hadoop Distributed File System): Manage distributed storage for large datasets.
YARN (Resource Manager): Allocate system resources to different tasks.
Hive Metastore with RDBMS: Hive is used for querying and managing large datasets. Youll configure it with an RDBMS (like MySQL or PostgreSQL) as its metastore.
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, youll import data into HDFS. This is a critical task as youll manage and ensure the integrity and flow of large datasets into the Hadoop cluster for processing.
Experience with data ingestion tools like Kafka and Sqoop.
This role combines deep technical expertise in Hadoop infrastructure with strong operational management and troubleshooting skills, all while ensuring security and smooth deployments within a big data environment.
Experience working in an agile development environment.
