About Me

Over 3 years of experience in IT industry with Configuration Management, Release/Build Management, System Administration, Support and Maintenance in like RHEL, Ubuntu expertise in Automating build and deployment process using Shell scripts with focus...ike RHEL, Ubuntu expertise in Automating build and deployment process using Shell scripts with focus on DevOps tools and AWS Cloud. Extensively worked on Jenkins by installing, configuring and maintaining for Continuous integration (CI) and for End to End automation for all build and deployments. Implemented AWS Cloud platform and its features which includes EC2, VPC, EBS, AMI, SNS, RDS, EBS, Cloud Watch, Cloud Formation Autos calling, Cloud Front, IAM, S3, R53. Created infrastructure in a coded manner (infrastructure as code) using Ansible for configuration management of Remote servers Deployment of Cloud service including Jenkins and Nexus on Docker using Terraform. To achieve Continuous Delivery goal on high scalable environment, used Docker coupled with load-balancing tool Nginx. Used Kubernetes to orchestrate the deployment, scaling and management of Docker Containers. Developed and Maintained automate CI/CD Pipeline for code Deployment using Jenkins Basic Knowledge of SAP B1, B1 HANA, SAP S4 HANA Administration Provided 24/7 Production and Coordinated with Developers, Management and End-Users to Resolve critical issues Certification: Certified Masters Big Data Engineer Program in collaboration with IBM Training Experience: Simplilearn Big Data Hadoop and Spark Developer Bid Data Hadoop Administration MongoDB Developer and Administration 8 Months of Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets Experience with the Hadoop stack (MapReduce, Spark, HDFS, Sqoop, Pig, Hive, HBase, Flume, Zookeeper, impala Proven experience in developing Big Data Pipelines in a Hadoop Ecosystem using Kafka, Hive, HDFS, HBase, and Spark on Yarn Knowledge of Hadoop Architecture Distributed Storage (HDFS) and YARN, Data Ingestion into Big Data Systems and ETL Performed Distributed Processing MapReduce Framework and Pig and Processing NoSQL Databases HBase Knowledge of Spark Core Processing RDD and Spark SQL Processing Data Frames Spark Modelling Big Data with Spark and Stream Processing Frameworks and Spark Streaming Spark Graph X HDFS Hadoop Distributed File System and Hadoop Cluster Setup and Working Hadoop Cluster Maintenance and Administration and Hadoop Computational Frameworks Scheduling Managing Resources Performing Hadoop Cluster Planning Hadoop Clients and Hue Interface Data Ingestion in Hadoop Cluster Managing Hadoop Ecosystem Components Services, Hadoop Security, and Cluster Monitoring Knowledge of CRUD Operations in MongoDB Developing Java and Node JS Application with MongoDB and Administration of MongoDB Cluster Operations