Senior 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. The operating model is a federated model with Core Engineering teams based in London/Bucharest/Bangalore and Engineers embedded within each Business division to drive adoption, automation, and platform engineering best practices.

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.
• Automate operational tasks, deployments, monitoring, and infrastructure provisioning using Python and Terraform.
• 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,
• Python - 5+ years of experience developing automation scripts, deployment utilities, infrastructure tooling, and operational automation using Python.
• 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.
• Terraform - 3+ years of experience provisioning and managing AWS infrastructure using Terraform. - Experience developing reusable Terraform modules and managing remote state.
• 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