OBJECTIVE:

• Professional DevOps Engineer with 8 Years of extensive experience with Infrastructure Administration in LINUX (RHEL/CENTOS 5/6/7, Ubuntu), Windows Server 2008 R2/2012 R2, Amazon Web Services, Azure and Tools that are used for Automation of Configuration Management in a CI/CD (Continuous Integration & Deployment/Delivery) Pipeline under DevOps Culture.
• Strong skills in source code repository tools such as GIT, Clear Case, and SVN, Expertise in build with Ant, Maven, GIT, Jenkins, cruise control
• Good experience on DevOps tools such as Chef, Vagrant, Oracle Virtual Box, Puppet, Jenkins, Maven, ANT, SVN, GIT and Docker.
• Working Experience on Azure Databricks cloud to organizing the data into notebooks and making it easy to visualize data through the use of dashboards.
• Good experience in working with complex Datasets using EC2 - Cron jobs, SQL, Confidential, Databricks, Confidential .
• Configuring the Docker containers and creating Docker files for different environments, on building
• Hands on experience in build and deployment for Dot net based and Java applications.
• Experience in authoring pom.xml files, perform releases with MAVEN and ANT release plugins, and manage artifacts (jar, war & ear) from source code in Sona type NEXUS repository.
• Worked with Puppet Enterprise and Puppet Open Source. Installed, configured, upgraded and managed Puppet Master. Integration of Puppet with Apache and Passenger.
• Familiarity with Azure Cloud Solutions and architectures (Windows/Linux VM's, Data Lake, HDInsight, SQL Database, Virtual Network, Azure AD)
• Experience in System Administration, System Builds, Server builds, Installs, Upgrades, Patches, Migration, Troubleshooting, Security, Backup, Disaster Recovery, Performance Monitoring and Fine-tuning on UNIX Red Hat Linux System.
• Good understanding of the principles and best practices of Software Configuration Management (SCM) in Agile, scrum, and Waterfall methodologies.

TECHNICAL SKILLS

• .Net
• Visual Studio
• Apache Spark
• API
• Application Server
• C#
• Continuous Integration/Delivery
• CI/CD
• Continuous Integration
• Git
• Gradle
• Groovy
• GUI
• Hadoop
• Hbase
• HDFS
• Hive
• JavaScript
• Jenkins
• JSON
• Middleware
• Perl
• PHP
• Unspecified
• Pig
• Python
• Flask
• Pandas
• Ruby
• Scripting
• Subversion
• SVN
• XML
• Zookeeper
• Amazon Elastic Compute Cloud
• EC2
• Amazon Elastic Mapreduce
• Amazon Emr
• Amazon Web Services
• AWS
• Asteradata
• Cassandra
• Docker
• Kubernetes
• Microsoft SQL Azure
• SQL Azure
• Microsoft Windows Azure
• Windows Azure
• Mongodb
• Openshift
• Serverless Architecture
• Serverless
• Terraform
• Data Migration
• Database Administration
• MS SQL Server
• SQL Server
• MySQL
• Oracle
• SQL
• CHEF
• Chef Server
• Clustering
• DEV OPS
• Devops
• DNS
• IIS
• Nagios
• Network Security
• Puppet
• Remedy
• Site Reliability Engineer
• System Administration
• Virtualization
• Apache
• Linux
• RED HAT
• Shell Scripting
• Shell Scripts
• Unix/Linux
• Amazon Dynamodb
• Dynamodb
• Apache Hadoop HDFS
• Apache Hadoop Oozie
• Oozie
• Datasets
• ETL
• Hadoop Cluster
• JBoss
• Kafka
• Software as a Service
• SAAS
• Splunk
• Confidential
• Hdinsight
• IAAS
• PAAS
• Provisioning
• Virtual Machine
• VM
• ANT
• Change Management
• Configuration Management
• Clear Case
• Clearquest
• Deployment
• Maven
• Software Configuration
• Software Configuration Management
• Internet Information Services
• Security
• Tomcat
• Web Services
• Web Sphere
• Weblogic
• WebSphere
• JIRA
• Junit
• VMS
• Java
• Disaster Recovery
• Kerberos
• Tokens
• User Access
• Infrastructure Management
• Systems Administration
• Vmware
• Application Design
• EMR
• SCRUM
• Version Control
• T-SQL
• Data Warehouse
• HDS Cruise Control
• Cruise Control
• Open Source
• Real-Time
• Graphical User Interface
• SAP
• R2
• ARM
• Containerization
• Reliability Engineer
• ECS
• Subject Matter Expert
• SME
• Ecosystem
• Nexus
• Asset Management
• Investment Banking
• IPO
• Initial Public Offering
• Securities
• Pipeline
• Microsoft Windows
• Windows Server 2008
• Windows Server 2008 R2
• MAC
• Integrator
• Integration
• Documentation
• DOT
• Chef (All)
• Security Policies
• Workflow
• Production Environment
• Wealth Management
• Best Practices
• QA

PROFESSIONAL EXPERIENCE

Confidential

Sr. Cloud Devops Engineer

Responsibilities:

• Installed and Configured Kubernetes, Chef Server/Workstation, and nodes via CLI tools and wrote Docker files to create new images based on working environments for testing purposes before deployment.
• Successfully setup Input and Output file configurations, database connectivity on Confidential / S3 buckets using JSON workflows in Quantum environment.
• Created Python / SQL scripts, to transform Databricks notebooks from Confidential table into Confidential S3 buckets.
• Deployed an Azure Databricks workspace to an existing virtual network that has public and private subnets and properly configured network security groups.
• Extract Transform and Load data from Sources Systems to Azure Data Storage services using a combination of Azure Data Factory, T-SQL, Spark SQL and U-SQL Azure Data Lake Analytics Generated SQL Scripts using python to extract Structured and non-structured data from various platforms Confidential, Databricks. Fetched data from Confidential data warehouse and performed ETL on the platform.
• Created ansible playbooks & roles for configuring applications like tomcat, MYSQL etc.
• Installation and configuration of Apache, Tomcat, MYSQL, SQL server. Create or update Azure resource group, Key Vault, Function, API management services.
• Monitoring and implementing security on Azure IAAS VMs and virtual networks.
• Design Setup maintain Administraor the Azure SQL Database, Azure Analysis Service, Azure SQL Data warehouse, Azure Data Factory, Azure SQL Data warehouse Implemented cloud services IAAS, PAAS, and SaaS which include Open stack, OpenShift, Docker Deploying Azure IaaS virtual machines (VMs) and Cloud services (PaaS role instances) into secure VNets and subnets.
• Created Hadoop clusters in Cloud platform Microsoft AZURE and also created HBase and Hive Tables, created Kerberos key tabs, principals and refreshed the tokens, created HDFS directories and copied data into them.
• Worked on analyzing Hadoop cluster using different big data analytic tools including Flume, Pig, Hive, HBase, Oozie, Zookeeper, Spark and Kafka. Experience in Microsoft Windows operating systems, some experience with Linux and Mac.
• Expertise in administering application servers, web servers (Tomcat, JBoss, Microsoft IIS, Apache) Good Experience in Microsoft Azure. Worked with ARM Modules, Python Scripts, Azure Cli Scripts to write Runbooks and automate many things in the Azure Cloud.
• Used python for serverless functions in aws using lamdba and Azure Funct

Confidential

DevOps Engineer

Responsibilities:

• Continuous monitoring by creating rules and alerts using Azure Monitor. Working on Azure Admin tasks like provide access AAD, create VMs, create Oracle DB, Cosmos DB, Function Apps, APIM etc.
• Worked on big data (Hadoop) environment with exposure to HIVE, Spark, Cassandra, SQL and ETL components.
• Used Python exports and datastructures for a tool called Promethues where we monitor our entire build and Release Pipeline Management Expertise with Microsoft technology (Visual Studio, TFS, SQL Server, Windows Server)
• Experience in application design, development, delivery and support on Microsoft Windows platform Windows, IIS, SQL Server, .net Excellent knowledge to create Azure DevOps Build CI pipeline with verity of Repositories (GitHub, Azure Repo and VM).
• Responsible for estimating the cluster size, monitoring and troubleshooting of the Spark databricks cluster.
• Worked on Azure Databricks to use custom DNS and configure network security group ( Confidential ) rules to specify egress traffic restrictions.
• Secured sensitive data like DB passwords and BitBucket passwords with Ansible Vault.
• Wrote Ansible playbooks to launch and Automate AWS instances on Ubuntu, Amazon Linux and RHEL.
• Provisioned Servers and deployed features using Ansible.
• Troubleshooting pipelines submitted using Apache Spark and Hadoop services.
• Implemented CI/CD pipelines on Azure Devops, provisioning Azure Resources, creating resources using ARM templates, creating different stages of deployment pipelines using pipeline tasks & groups, powershell Developing Azure ARM templates and deploying using Azure DevOps to provision the Infrastructure.
• Used Azure ARM templates, Bash Shell for implementing infrastructure as a code Create/Refresh/reuse Azure DevOps CI/CD pipeline based on requirement.
• Worked on the Docker ecosystem with a bunch of open source tool like Docker machine, Docker Compose, Docker Swarm. Involved in Data Migration using SQL, SQL Azure, Azure storage, and Azure Data Factory, SSIS, PowerShell Developed auto container to automate containerization of new and existing applications as well as deployment and management of complex run time environment like Kubernates.
• Create or update Azure resource group, Key Vault, Function, API management services.

Environment: Jenkins, Docker, Linux, Azure Data Factory, SSIS, Powershell, Azure SQL, Ubuntu, ARM Templates, Bash & Shell Scripting, Chef, Ansible, Kuberneates, Jira, GIT, Restful API's.

Confidential

Devops Engineer/Build and Release Engineer

Responsibilities:

• Responsible for administrating and maintaining of Kubernetes Clusters( Confidential -engine and Confidential ) hosted in Microsoft Azure.
• Configured VM's availability sets using AZURE portal to provide resiliency for IaaS based solution and scale sets using AZURE Resource Manager to manage network traffic.
• Monitoring and implementing security on Azure IAAS VMs and virtual networks.
• Migrated the application from Infrastructure as a Service (IaaS) to Platform as a Service (PaaS) by converting existing solution to Windows Azure Worker Role.
• Implemented and responsible to be primary SME on Azure services including SaaS, PaaS and IaaS while contributing Creating Spark clusters and configuring high concurrency clusters using Azure Databricks to speed up the preparation of high-quality data.
• Implemented Hadoop clusters on processing big data pipelines using Amazon EMR and Cloudera whereas it depended on Apache Spark for fast processing and for the integration of APIs Experience with Scripting or programming languages C# or Powershell Worked as shadow with project leads on Dot Net applications build and deployments using MS build.
• Develop and implement an automated Linux infrastructure using Puppet.
• Expertise with Jenkins CI, maintained fully automated CI/CD pipelines with Groovy script and resolved build failures.
• Worked on python script to remove monitored machines from Zabbix server that has terminated from AWS console as well.
• Implemented Copy activity, Custom Azure Data Factory Pipeline Activities for On-cloud ETL processing Created detailed documentation of complex build and release process, post release activities process, JIRA workflow and Release notes.
• Involved in working with Python Openstack API's.
• Used Remedy, Jira as deployment issue tracking tool Worked for Kafka cluster setup using Ansible and Jenkins. Designed Continues Delivery platform using Jenkins, Bit Bucket, Artifactory and Ansible tower.
• Created Jenkins web hooks in BitBucket for push notifications to Jenkins Created BitBucket repositories and Managed BitBucket user access and branch permissions.
• Build CI/CD pipelines to deploy Azure SQl Components and ingest data into it using Python Pandas.
• Developed APIs using Python Flask and deployed on Azure App Service.
• Performed Builds using MS Build and Devin command line for C#, VB, DOT NET Applications Exposed Virtual machines and cloud services in the VNet to the Internet using Azure External Load Balancer.
• Configured Azure Virtual Networks, subnets, Azure network settings, CDIR address blocks, DNS settings, security policies.

Confidential

Cloud Engineer/ DevOps Engineer

Responsibilities:

• Cloud support team working 24/7 resolving user virtual image VM issues Developed automation scripting in Python (core) using Puppet to deploy and manage Java applications across Linux servers.
• Created Master-Slave configuration using existing Linux machines and EC2 instances to implement multiple parallel builds through a build farm.
• Worked with ARM MOdules, Python Scripts, Azure Cli Scripts to write Runbooks and automate many things in the Azure Cloud.
• Worked with Terraform Templates to automate the Azure IaaS virtual machines using terraform modules and deployed virtual machine scale sets in various environments.
• Continuous monitoring by creating rules and alerts using Azure Monitor.
• Create/Refresh/reuse Azure DevOps CI/CD pipeline based on requirement.
• Use RDS, MySQL and DynamoDB to perform basic database administration.
• Ensured all steps are successfully completed and document their completion times and issue logs.
• Adding new Virtual Machine on to the Cloud Created Multi-Masters and Multiple worker Kubernates cluster for Production environment
• Worked with OpenShift platform in managing Docker containers and Kubernates Clusters.
• Wrote Power shell scripts for Dot Net application deploys, service installs and for windows patches/upgrades Following the documentation, plan of action to resolve VM Bulk Installation of application on Virtual Machines such as Oracle, SQL Server, Linux Operating System, Java, .Net, and in-house developed application
• Developing the system as per the documentation provided

Environment: Ubuntu, Chef, MySQL, DynamoDB, Python, Shell, VMware, Java, Ant, Maven, Jenkins, Hudson, GIT, SVN, Apache Webserver, JBoss, GIT, SVN, Windows, Ruby, Chef, JIRA.

Confidential

DevOps Engineer/Site Reliability Engineer

Responsibilities:

• Migrated and maintained build and test environments into the Cloud Infrastructure.
• Developed Cloud Formation scripts to automate EC2 instances and created versions for the updated script and also wrote scripts in Terraform and Lambda to spin up EC2 instances.
• Created Docker images using a Docker file, worked on Docker container snapshots, removing images and managing Docker volumes.
• Designed and implemented CI (Continuous Integration) system, configuring Jenkins servers, Jenkins nodes, creating required scripts (Perl & Python).
• Used Data Lake to store relational data like operational databases and data from line of business applications.
• Worked on Data Lakes which allowed us to import any amount of data that can come in real-time.
• Implemented AWS infrastructure management as IaaC using Terraform, Gitlab, DynamoDB and S3 service.
• Configured Git with Jenkins and schedule jobs using POLL SCM option and also integrated to automate the code checkout process.
• Configuring Jenkins as a common CI engine to build and promote applications to DEV, QA and STAGING to Linux environments.
• Highly involved in Configuring, monitoring and multi-platform servers by defining Chef server from workstation to manage and configure Chef nodes.

Environment: EC2, Perl, Data Lake, Docker, CI, Python, PAAS, Openshift, Kubernetes, Terraform, Gitlab, Chef.