• Design, build, and maintain scalable ETL pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics to support data ingestion, transformation, and storage.• Integrate data from various sources (structured and unstructured) into Azure data lakes or data warehouses, ensuring seamless data flow across different business units.• Implement and manage Azure-based storage solutions like Azure Data Lake Storage (ADLS) and Azure SQL Database, focusing on performance optimization and cost-efficiency.• Ensure data security by implementing Azure RBAC (Role-Based Access Control), encryption (Azure Key Vault), and compliance with industry regulations like GDPR and HIPAA.• Utilize Azure Stream Analytics and Azure Event Hubs for real-time data processing and analytics, providing business insights on-the-go. Monitor data workflows and optimize them for performance and cost efficiency using Azure Monitor, Log Analytics, and Azure Cost Management tools.• Work closely with data science teams to deploy machine learning models on Azure Machine Learning and integrate them into business operations using data.• Automate deployment processes using Azure DevOps, ensuring smooth code integration and continuous delivery for data solutions.• Develop and automate administrative tasks and processes within the Azure environment using PowerShell scripts, such as managing data pipelines, scheduling tasks, and automating infrastructure provisioning.• Work with Linux-based systems to deploy, monitor, and manage large-scale data processing environments in Azure. This includes configuring services like Apache Hadoop and Spark on Linux virtual machines or Azure Databricks.• Use PowerShell and Python to define infrastructure as code, automating the provisioning of data engineering resources on Azure, and managing deployments efficiently.

• Design, deploy, and manage AWS infrastructure using services such as EC2, S3, RDS, VPC, and Lambda and Implement Infrastructure as Code (IaC) using tools like AWS CloudFormation or Terraform• Develop and maintain CI/CD pipelines to automate the deployment of applications and infrastructure changes using AWS CodePipeline, Jenkins, GitLab CI, or similar tools.• Automate repetitive tasks and streamline deployment processes using scripting languages (e.g., Python, Bash).• Implement monitoring and logging solutions using AWS CloudWatch, AWS X-Ray, and third-party tools to ensure system reliability and performance.• Ensure compliance with security best practices and regulatory requirements, including data protection and access control using AWS IAM and AWS KMS.• Collaborate with development teams to understand application requirements and provide guidance on best practices for AWS infrastructure and Document infrastructure designs, configurations, and processes to ensure knowledge sharing and maintainability.• Design and implement disaster recovery plans and high-availability solutions using AWS services such as AWS Backup and AWS Elastic Load Balancing.• Manage and configure servers and environments using tools like Ansible, Chef, or Puppet and Deploy applications to AWS environments using AWS Elastic Beanstalk, ECS, EKS, or similar services.• Managed both framework and CloudFormation to automate AWS environment creation along with the ability to deployment on AWS, using build scripts (AWSCLI) and automate solutions using Shell and Python.• Worked on creating the Virtualization of the servers on AWS with the use of tools like Docker, build the Docker image and version control to meet the objective of Continuous Delivery goal on a highly scalable environment. Also had a hands on experienced with load-balancing tool Nginx.

• Deployed the code and provisioning the cloud Environments cloud tool like VSTS and Micro service.• Have knowledge on partition of Kafka messages and setting up the replication factors in Kafka Cluster.• Implemented various resources in Azure using Azure portal, PowerShell on Azure Resources Manager deployment models. Experience deploying infrastructure as code applications using ARM Templates (JSON).• Moved all Kubernetes container logs, application logs, event logs and cluster logs, activity logs and diagnostic logs into Azure Event Hubs and then into Splunk for monitoring Daily monitoring production servers using Grafana and Prometheus which is integrated with Kubernetes, exceptions and report to the team if something happen during standups Worked on Configuring the ELKstack and used it for analyzing the logs from different applications.• Extended support for existing product teams on how to integrate CI/CD into development life cycle Streamlined installation of Open Shift on partner cloud infrastructure such Azure• Defined dependencies and plugins in Maven (Pom.xml) Java files for various activities and integrated Maven with GIT to manage and deploy project related tags and administrated Artifactory repository.• Managing Azure DevOps build and release pipeline. Setting up new repos managing the permissions for various GIT branches. Deployed microservices, including provisioning AZURE environment Creating JIRA confluence articles for recent development performed POC and tech designs.• Experienced in Performed back-ups, scan states and load states of user's profile during the Azure migration process.

• Involved in implementing and Administrating enterprise level data backups and Data Recovery.• Maintained maximum uptime and maximum performance capacity for Enterprise Production, QA, and UAT/Staging.• Installation and configuration of engine to maintain standard configuration and security policies in the server farm.• Developed and supported the Red Hat Enterprise Linux based infrastructure in the cloud environment.• Configuring network services such as DNS/NFS/NIS/NTP for UNIX/Linux Servers. Accomplished User administration of UNIX / Linux account using SeOS Experience with NoSQL, MongoDB. Automated tasks using Korn, Bash Shell scripts. Installation Linux system. Scaling complex SaaS for web services.• Used JIRA tool to track all the defects and changes related to build and Release Team.• Deployed code on Web Sphere application servers for Production, QA, and Development environments.• Worked on creating the Docker containers and Docker consoles for managing the application life cycle• Deployed web applications using Chef by developing the cookbook. Also responsible for creating and importing all the environments required running the project.• Focused on automation and continuous integration. Automated local development environment using Chef.• Designed roles and groups for users and resources using AWS Identity Access Management (IAM).• Created Development Environments in Amazon Web Services using services like VPC, ELB, EC2 and RDS instances.