AWS Cloud Engineer Resume

TECHNICAL SKILLS

Cloud: AWS

Operating Systems: RHEL 5/6/7, Windows server2012/2016, Solaris 8/9/10/11

Network Protocols: TCP/IP Suite, UDP, HTTP/HTTPS, SSL, SMTP, FTP IMAP, POP3, NIS, NIS+, NFS, DNS, DHCP, LAN/WAN

Hardware: Memory Optimized c4, c3,c5, c5d, cc2,c5n, c5ad, c6, c1.medium, c6gd.metal..ect Storage Optimized d2.2xlarge,d2.4xlarge,d2.xlarge, d2.8xlarge, i3.4xlarge, i3, hs1 Accelerated Computing like g3.4xlarge,g3.8xlarge,g3.16xlarge,p3,g3n,f1,g4dn,p3dn...etc HP DL 360, DL380,ML350, Sun Oracle Sparc E25k, E15k, E2900, Sparc T Series based servers

RDBMS: Oracle 8i/9i, 10g, 11g, 12c, DynmoDB, MongoDB, Postgresql, MySQL, Nosql, MS Access 2000

Applications: Wordpress, Apachi Tomcat, RabbitMQ, LAMP, PHP, Sercive Now, Websphere, Netbackup, TSM, Filenet P8, Maximo, AMI, Dockers, Kubernetes.

PROFESSIONAL EXPERIENCE

Confidential

AWS Cloud Engineer

Responsibilities:

Managed 512 EC2, total foot print of 1828 CPU power and 16 petabyte of storage in the Redhat Enterprise linux, Windows, SUSE and Amazon Linux 2 environments.
Worked and managed AWS services as EC2, RDS, API Gateway, Lambda, DynamoDB, Elastic Cache, ECS, ALB/NLB Load Balancers, S3, EBS, VPC, Secret Manager, Parameter Store Endpoints, Endpoint Services ...etc.
Strong working experience in Networking using Direct connect, TGW and Datacenters connectivity.
Worked on hardware - accelerated instances featuring GPUs, FPGAs, and our own custom ML inference chip, AWS Inferentia. g3.4xlarge,g3.8xlarge,g3.16xlarge,G4dn instances offer the best price/performance for GPU based ML inference, training less-complex ML models, graphics applications others that need access to NVIDIA libraries such as CUDA, CuDNN and NVENC.
Created Cloud Landing Zone setup using AWS Cloud Native services and third party solutions .
Monitored the instances with Cloud Watch Monitoring and implementation using enterprise tools and Automation configuration management tools like chef, Puppet, SSM etc.
Worked on containers using AWS container services ECS and EKS.
Strong knowledge of cloud programming skill with experience in AWS Lambda functions and other scripting languages like Python, Bash, Nodejs and JAVA to automate resource creation.
Worked and managed AWS CLI, Cloud formation, AWS CDK, Terraform, Ansible with troubleshooting experiences
Strong knowledge of Cloud Security practices and IAM Policy preparation for AWS, CloudTrail, Guard Duty, Macie, AWS Config, AWS inspector etc
Planned designed and worked with Amazon Web Services EC2 - including ec2 type A1, T3, T2, M5, M5a, M4, T3a running on Inetl and AMD based CPUs.
Worked on EBS volume types including IO1,GP2,ST1,SC1 useded for Highest performance SSD and High volume workloads HDDs designed for latency-sensitive transactional workloads for I/O-intensive NoSQL and relational databases and Big data, data warehouses, log processing respectively.

Confidential

AWS Cloud Engineer

Responsibilities:

Worked in tandem with engineering team to identify and implement the most optimal cloud-based solutions for the company.
Worked on accelatated cpu compute instances like C4, C3, C5, C5d with optomized mem and stoage which includes P3, G3n, F1 and D2.xlarge, D2.8xlarge, I3.4xlarge, I3, Hs1 respectively.
Experience to have install LAMP web servers, WordPress blogs, Configure SSL/TLS on Amazon Linux 2/RHEL/SUSE and clustring and High availability of any application.
Planned, designed and managed AWS cloud-based services including IAM, EC2, RDS, EKS, S3.
Managed AWS cloud environments in accordance with company security guidelines.
Deployed and debuged cloud initiatives as needed in accordance with best practices throughout the development lifecycle.
Employed exceptional problem-solving skills, with the ability to see and solve issues before they snowball into problems.
Used extensive knowledge of SSO, IAM, VPC, Subnets, IGW, NATGW, DNS, Load Balancing, AWS Certificate Manager, and AMI.
Built and designed web services in the cloud, along with implementing the set-up of geographically redundant services.
Extensive knowledge of Orchestration and automation, using Puppet and Ansible, of cloud-based platforms throughout the company.
Used Docker for containerization and Kubernetes for cluster container management solution.
Built applications, ran applications, and ran services with serverless architecture such as Lambda functions, API Gateway, Kinesis.
Automation scripting in Python, Go, Ruby, or Java.
Managed to stay current with industry trends, making recommendations as needed to help the company excel.
For Backup and recovery of EBS volumes using Amazon EBS snapshots, and create an Amazon Machine Image (AMI) from your instance to save the configuration as a template for launching future instances

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