Job
Description
Grade Level (for internal use): 10 S&P Global Commodity Insights The Role: Senior Cloud Engineer The Location: Hyderabad, Gurgaon The Team: The Cloud Engineering Team is responsible for designing, implementing, and maintaining cloud infrastructure that supports various applications and services within the S&P Global Commodity Insights organization. This team collaborates closely with data science, application development, and security teams to ensure the reliability, security, and scalability of our cloud solutions. The Impact: As a Cloud Engineer, you will play a vital role in deploying and managing cloud infrastructure that supports our strategic initiatives. Your expertise in AWS and cloud technologies will help streamline operations, enhance service delivery, and ensure the security and compliance of our environments. Whats in it for you: This position offers the opportunity to work on cutting-edge cloud technologies and collaborate with various teams across the organization. You will gain exposure to multiple S&P Commodity Insights Divisions and contribute to projects that have a significant impact on the business. This role opens doors for tremendous career opportunities within S&P Global. Responsibilities: Design and deploy cloud infrastructure using core AWS services such as EC2, S3, RDS, IAM, VPC, and CloudFront, ensuring high availability and fault tolerance. Deploy, manage, and scale Kubernetes clusters using Amazon EKS, ensuring high availability, secure networking, and efficient resource utilization. Develop secure, compliant AWS environments by configuring IAM roles/policies, KMS encryption, security groups, and VPC endpoints. Configure logging, monitoring, and alerting with CloudWatch, CloudTrail, and GuardDuty to support observability and incident response. Enforce security and compliance controls via IAM policy audits, patching schedules, and automated backup strategies. Monitor infrastructure health, respond to incidents, and maintain SLAs through proactive alerting and runbook execution. Collaborate with data science teams to deploy machine learning models using Amazon SageMaker, managing model training, hosting, and monitoring. Automate and schedule data processing workflows using AWS Glue, Step Functions, Lambda, and EventBridge to support ML pipelines. Optimize infrastructure for cost and performance using AWS Compute Optimizer, CloudWatch metrics, auto-scaling, and Reserved Instances/Savings Plans. Write and maintain Infrastructure as Code (IaC) using Terraform or AWS CloudFormation for repeatable, automated infrastructure deployments. Implement disaster recovery, backups, and versioned deployments using S3 versioning, RDS snapshots, and CloudFormation change sets. Set up and manage CI/CD pipelines using AWS services like CodePipeline, CodeBuild, and CodeDeploy to support application and model deployments. Manage and optimize real-time inference pipelines using SageMaker Endpoints, Amazon Bedrock, and Lambda with API Gateway to ensure reliable, scalable model serving. Support containerized AI workloads using Amazon ECS or EKS, including model serving and microservices for AI-based features. Collaborate with SecOps and SRE teams to uphold security baselines, manage change control, and conduct root cause analysis for outages. Participate in code reviews, design discussions, and architectural planning to ensure scalable and maintainable cloud infrastructure. Maintain accurate and up-to-date infrastructure documentation, including architecture diagrams, access control policies, and deployment processes. Collaborate cross-functionally with application, data, and security teams to align cloud solutions with business and technical goals. Stay current with AWS and AI/ML advancements, suggesting improvements or new service adoption where applicable. What Were Looking For: Strong understanding of cloud infrastructure, particularly AWS services and Kubernetes. Proven experience in deploying and managing cloud solutions in a collaborative Agile environment. Ability to present technical concepts to both business and technical audiences. Excellent multi-tasking skills and the ability to manage multiple projects under tight deadlines. Basic Qualifications: BA/BS in computer science, information technology, or a related field. 5+ years of experience in cloud engineering or related roles, specifically with AWS. Experience with Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation. Knowledge of container orchestration and microservices architecture. Familiarity with security best practices in cloud environments. Preferred Qualifications: Extensive Hands-on Experience with AWS Services. Excellent problem-solving skills and the ability to work independently as well as part of a team. Strong communication skills and the ability to influence stakeholders at all levels. Experience with greenfield projects and building cloud infrastructure from scratch. Benefits: Health & Wellness: Health care coverage designed for the mind and body. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: Its not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awardssmall perks can make a big difference.
