Detailed JD (Roles and Responsibilities)

Candidate with Total 12+ years experience with below details:

- Mandatory Technical Skill : AWS Admin , Terraform , CI/CD
- Cloud DevOps Expertise: 5+ years designing and managing automated DevOps workflows for large-scale cloud environments.
- AWS Services Mastery: Hands-on experience with EC2, EKS, S3, VPC, IAM, CloudFormation.
- Infrastructure as Code (IaC): Advanced proficiency in Terraform for multi-stack deployments using modular design and best practices.
- CI/CD Automation: Proven experience building end-to-end automated release management platforms for IaC and Databricks pipelines using GitHub Actions, Jenkins, AWS CodePipeline.
- Integrated CI/CD Components:
- Code Quality & Security Scanning: Tools like SonarQube or similar.
- Automated Testing Frameworks: For Databricks notebooks and workflows.
- Approval Workflows: Integrated gates for compliance and governance.
- Integration with ITSM & Project Tools: ServiceNow, Jira for change management and ticketing.
- Release Management Platforms: Hands-on experience with tools like Harness, ArgoCD, or similar for deployment orchestration.

- Audit Logging & Dashboards: Ability to set up audit logs, dashboards, and capture CI/CD metrics for compliance and performance monitoring.
- Infrastructure Planning & Scaling:



Experience in planning and scaling infrastructure behind CI/CD pipelines for high availability and performance.
- Databricks Architecture & Configuration: Robust experience with Databricks Lakehouse Platform, including Unity Catalog and Delta Lake.
- Kubernetes Expertise: Ability to design and operate robust, scalable EKS clusters.
- Observability & Monitoring: Expertise in CloudWatch, Prometheus, ELK stack.
- Disaster Recovery & High Availability: Experience implementing DR and HA strategies.

1. - Should Have

- Databricks AI Features: Familiarity with Model Serving, Feature Store, MLflow.
- AWS AI/ML Services: SageMaker, Bedrock.
- DevOps for AI Agents & Models: Experience automating ML model lifecycle, including training, deployment, monitoring, and rollback strategies for AI agents and models.
- Cost Optimization: AWS pricing strategies.
- Serverless Architectures: Lambda, API Gateway.
- Platform as a Service (PaaS): Knowledge of AWS PaaS offerings (Elastic Beanstalk, Fargate) and integration patterns.

1. - Nice to Have

- AWS DevOps Engineer Professional Certification.
- Containerization: ECS, EKS, Docker.
- Terraform Certification.
- Strong communication skills.

Total Experience

12+ years

📌 AWS,Terraform_India (India)
🏢 Clifyx
📍 India