●       Have good knowledge of Microsoft Azure services like Azure Networking, Azure Virtual Machines, Network Security Group, Virtual Networking, Virtual Network Peering, Azure Load Balancer, Azure Storage, Azure Functions, Azure App Services, Azure API Management – Build deploy APIs and Consume APIs, Azure Container Services, Azure Active Directory, Azure AD Connect, Azure SQL & Cosmos DB etc.

●       Have good knowledge of Google Cloud Platform services like Load Balancer, Auto scaling, Storage, VPC, GCP cloud, Google App Engine, Cloud SQL, Data store, Spanner, Google Kubernetes Engine.

●       Have good knowledge of AWS services like EC2, VPC, S3, Route53, Auto Scaling, IAM, Athena and SQS/SNS, Elastic Cache, Glue, Cloud watch.

●       Have good knowledge of Big Data Management & Analytics AWS services like RDBMS, NoSQL, DynamoDB, Table, Index, Key, Auto Scaling, Global Table, QDD, DAX, Cassandra, Hadoop, EMR, Hive, Spark, Kafka etc.

●       Have good knowledge of Containers AWS services like Docker, ECS, ECR, Kubernetes.

●       Have good knowledge of load balancing for micro services AWS services.

●       Have good knowledge of cloud native DevOps Code Commit, Code Build, Code Deploy, Code Pipeline, Elastic Beanstalk, Cloud Trail.

●       Hands-on experience on implementing a team communication solution using Matter most and AWS using EC2, VPC, Security Group, NAT Gateway/ NAT Instance.

●        Hands-on experience on building an automated business process using Managed Services on a Public Cloud using Amazon S3, SNS, Athena, DynamoDB, AWS S3, AWS SNS, AWS RDS, Python, Boto3.

●       Hands-on experience on Create and Manage a Nonrelational Database using AWS DynamoDB using DynamoDB, NoSQL, Python, Boto3, EC2.

●       Hands-on experience on Deploying web app using ECS Docker, ECS, Load Balancer, Far gate.

●       Programming in C and C++ language.

●       JAVA.

●       Software Testing Certification Course.

●       SQL and Relational Database 101.

●       Introduction to Data Science.