Cloud Engineer

The Expertise and Skills You Bring
    •    Bachelor’s or Master’s Degree in a technology-related field (e.g. Engineering, Computer Science, etc.) required.
    •    10+ years of hands-on experience designing, deploying, and operating production Kubernetes clusters (self-managed or managed services such as EKS, AKS, GKE).
    •    Deep expertise in Kubernetes internals: workload scheduling, RBAC, network policies, Helm/Kustomize, Operators, and cluster autoscaling.
    •    Strong experience with DevOps practices and tooling: CI/CD pipelines (Jenkins, GitHub Actions, ArgoCD / Flux GitOps), infrastructure-as-code (Terraform, Ansible), and container image management (Docker, container registries).
    •    Proven ability to build and maintain self-service developer platforms and golden-path templates on Kubernetes.
    •    2+ years of experience operating workloads on Cloud platforms (AWS, Azure, or Google Cloud Platform), including networking, IAM, and cost optimisation.
    •    Strong knowledge of observability: metrics (PrometheGrafana), logging (ELK / OpenSearch), and distributed tracing.
    •    Experience with service mesh technologies (Istio, Linkerd) and API gateway patterns.
    •    Solid experience in Agile methodologies (Kanban and SCRUM).
    •    Strong technical design and analysis skills; ability to deal with ambiguity and work in a fast-paced environment.
    •    Excellent communication skills, both written and verbal, with strong collaboration skills across multiple teams.
    •    3+ years of experience developing microservices with Java and Spring Boot.
    •    Strong understanding of microservices architecture, REST APIs, and event-driven design patterns.
    •    Experience containerising and deploying Java applications to Kubernetes, including JVM tuning for container environments.
    •    Familiarity with build tooling (Maven, Gradle) and code quality practices (unit/integration testing, static analysis).

Good to Have
    •    Experience with Apache Kafka: topic design, consumer groups, offset management, and schema evolution (Avro / Protobuf with Schema Registry).
    •    Familiarity with Kafka deployment and operations on Kubernetes (Strimzi Operator or Confluent Platform).
    •    Exposure to stream processing frameworks such as Kafka Streams, Apache Flink, or Spark Structured Streaming.

The Team
The Platform Engineering team within Enterprise Data & Artificial Intelligence business unit is responsible for assisting in the governance, design and delivery of applications utilizing the Event Streaming and Message Queueing platforms. Our vision is to enhance and streamline the onboarding experience while ensuring the highest quality of application readiness for our users.
The Senior Platform / DevOps Engineer will help deliver values such as
    •    Solution design, solving key technical challenges, and mentoring the team.
    •    Building and supporting mission critical applications to provide the best customer experience
    •    Exploring new technology trends and leveraging them to simplify our data ecosystem
    •    Driving Innovation and leading the team to implement solutions with future thinking
    •    Collaborating with internal and external teams to deliver technology solutions for the business needs
    •    Guiding teams to improve development agility and productivity
    •    Resolving technical roadblocks to the team and mitigating potential risks
    •    Delivering system automation by setting up continuous integration/continuous delivery pipelines
    •    Acting as a technical mentor to the team and bringing key knowledge and experience.

If you are intrestewd for this role , Please drop us a mail with your updated profile @