
Cloud Infrastructure Professional
3 days ago
We are seeking a highly skilled professional to design and manage cloud installations for large corporate houses.
The ideal candidate will have prior experience in backend and data engineering, automated deployment with CI/CD pipelines, shell scripting for automation, application load balancer configuration, dashboard creation, and data management.
Key responsibilities include:
- Backend and Data Engineering: Designing and managing backend APIs, creating dashboards, user interfaces, and developing data models to meet client requirements.
- Automated Deployment with CI/CD Pipelines: Experience working on Docker to containerize applications, managing Docker images in Docker Hub and ECR, and orchestrated deployments using AWS CodePipeline.
- Shell Scripting for Automation in CI/CD Pipelines: Creating shell scripts to automate the installation of dependencies and configurations in AWS CodePipeline.
- Application Load Balancer (ALB) Configuration: Configuring ALB to manage incoming traffic and enforce HTTPS protocol using AWS Certificate Manager (ACM).
- Dashboard Creation in AWS QuickSight and Power BI: Developing interactive dashboards to visualize unstructured data and integrate data from third-party APIs.
Additional responsibilities include:
- Data Management and Upsert Operations with AWS Glue and MySQL: Leveraging Python in AWS Lambda functions to establish seamless connections between AWS Glue and MySQL databases.
- Salesforce and AWS Integration: Engineered an integration solution for dynamic data synchronization between Salesforce and AWS.
- Infrastructure as Code with AWS CloudFormation: Launching multiple AWS services through CloudFormation templates.
- Design and Implementation of Real-Time Data Analytics Platform: Architected a scalable, real-time data analytics platform using AWS Glue, Redshift, and S3.
This is a unique opportunity to leverage your technical expertise and drive business growth.
The successful candidate will be well-versed in the following areas:
- Cloud infrastructure and architecture.
- Backend and data engineering.
- Automated deployment and CI/CD pipelines.
- Shell scripting and automation.
- Application load balancer configuration.
- Dashboard creation and visualization.
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