- Manage, administer, and maintain AWS cloud environments to ensure reliability, scalability, and performance.

- Design and develop scalable ETL/ELT data pipelines using AWS data engineering services.

- Work with S3, Glue, Redshift, and Athena to build and manage cloud-based data solutions.

- Implement and manage Infrastructure as Code (IaC) using Terraform and CloudFormation.

- Develop and maintain CI/CD automation using Jenkins and GitHub Actions.

- Develop data engineering and cloud automation solutions using Python, SQL, and PySpark.

- Manage IAM and cloud access configurations in AWS environments.

- Develop and maintain serverless solutions using AWS Lambda.

- Monitor AWS environments and workloads using CloudWatch.

- Work with Docker for containerization and deployment.

- Design and support Data Lake solutions and related cloud data platforms.

- Troubleshoot AWS, data pipeline, and DevOps-related issues and support ongoing cloud platform operations.

Skillset :

- Strong hands-on experience with AWS platform administration and cloud services.

- Experience with S3, Glue, Redshift, and Athena for cloud-based data engineering and analytics.

- Good understanding of IAM, Lambda, and CloudWatch for AWS access management, serverless workloads, and monitoring.

- Strong programming experience with Python, SQL, and PySpark.

- Hands-on experience developing and managing ETL/ELT data pipelines.

- Experience designing and implementing Data Lake solutions.

- Strong experience with Terraform and CloudFormation for Infrastructure as Code.

- Hands-on experience with Jenkins and GitHub Actions for CI/CD automation.

- Experience with Docker for containerized applications and workloads.

- Good understanding of AWS cloud operations, Data Engineering, and DevOps.