DevOps Engineer

Job Description

We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. Skills and Competencies Proficiency in Kubernetes and Amazon EKS (2+ years required): Essential for managing containerized applications and ensuring high availability and security in cloud-native environments. Strong expertise in AWS serverless technologies (required): Including Lambda, API Gateway, EventBridge, and Step Functions, to build scalable and cost-efficient solutions. Hands-on experience with Terraform (2+ years required): Critical for managing Infrastructure as Code (IaC) across multiple environments, ensuring consistency and repeatability. CI/CD pipeline development using GitHub Actions (required): Necessary for automating deployments and supporting agile development practices. Scripting skills in Python, Bash, or PowerShell (required): Enables automation of operational tasks and enhances infrastructure management capabilities. Experience with Databricks and Apache Kafka (preferred): Valuable for teams working with data pipelines, MLOps workflows, and event-driven architectures. Education bachelors degree in Computer Science or equivalent experience Responsibilities Design, automate, and manage scalable cloud infrastructure using Kubernetes, AWS, Terraform, and CI/CD pipelines . Design and manage cloud-native infrastructure using container orchestration platforms, ensuring high availability, scalability, and security across environments. Implement and maintain Infrastructure as Code (IaC) using tools like Terraform to provision and manage multi-environment cloud resources consistently and efficiently. Develop and optimize continuous integration and delivery (CI/CD) pipelines to automate application and infrastructure deployments, supporting agile development cycles. Monitor system performance and reliability by configuring observability tools for logging, alerting, and metrics collection, and proactively address operational issues. Collaborate with cross-functional teams to align infrastructure solutions with application requirements, ensuring seamless deployment and performance optimization. Document technical processes and architectural decisions through runbooks, diagrams, and knowledge-sharing resources to support operational continuity and team onboarding. We contribute to Moody s by: Accelerating data delivery and operational efficiency through automation, observability, and infrastructure-as-code practices that support near real-time data processing and remediation. Supporting data integrity and governance by enabling traceable, auditable, and resilient systems that align with regulatory compliance and GenAI readiness. Empowering innovation and analytics by maintaining a modular, interoperable platform that integrates internal and third-party data sources for downstream research models, client workflows, and product applications.