Platform/DevOps Engineer

Project description Our client is a global provider of financial market data, managing multiple change programs to deliver high-quality software that connects financial markets worldwide through real-time, high-frequency, low-latency data management systems. These projects are technically demanding and operate in a dynamic environment. The Markets and Corporate Engineering Divisions in our Client's company has embarked on a Data Science and AI/ML Transformation Program. The objective is to establish a new, centralized, and secure cloud-native platform Data Science and AI/ML on AWS to support modern application and infrastructure delivery. Responsibilities As a Senior DevOps Engineer , you will play a key role in designing, building, automating, and supporting cloud infrastructure and deployment pipelines across the Data Science and AI/ML platform. Design, implement, and manage highly available, secure, and scalable AWS infrastructure using Infrastructure as Code (IaC). Build, manage, and optimize CI/CD pipelines using GitLab (or equivalent tools) to enable automated application deployment. Deploy, configure, and maintain containerized applications using Docker and Kubernetes. Collaborate with development, architecture, and platform engineering teams to improve software delivery, reliability, and operational excellence. Support migration of applications and services to AWS cloud infrastructure. Implement security best practices, monitoring, logging, and disaster recovery strategies across cloud environments. SKILLS Must have Strong experience in DevOps engineering (8+ years preferred) designing, building, automating, and supporting cloud infrastructure and deployment pipelines across the Data Science and AI/ML platform. AWS - Strong hands-on experience with AWS services including SageMaker, Bedrock , EC2, VPC, IAM, S3, RDS and EKS, Docker & Kubernetes - Strong experience containerizing applications using Docker. - Hands-on experience deploying and managing Kubernetes clusters (preferably Amazon EKS). - Experience with Helm charts, Kubernetes networking, ingress controllers, autoscaling, and rolling deployments. GitLab CI/CD (or equivalent) - Strong experience designing and implementing CI/CD pipelines using GitLab CI/CD, Jenkins, GitHub Actions. - Experience implementing automated build, test, deployment, and release pipelines. Nice to have • Hands-on experience in using AI tools (e.g. GitHub Copilot) • Azure DevOps