Cloud Engineer
Role details
Job location
Tech stack
Requirements
Experience with Apache Kafka: topic design, consumer groups, offset management, and schema evolution (Avro / Protobuf with Schema Registry).
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Familiarity with Kafka deployment and operations on Kubernetes (Strimzi Operator or Confluent Platform).
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Exposure to stream processing frameworks such as Kafka Streams, Apache Flink, or Spark Structured Streaming., Bachelor's or Master's Degree in a technology-related field (e.g. Engineering, Computer Science, etc.) required.
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5+ years of hands-on experience designing, deploying, and operating production Kubernetes clusters (self-managed or managed services such as EKS, AKS, GKE).
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Deep expertise in Kubernetes internals: workload scheduling, RBAC, network policies, Helm/Kustomize, Operators, and cluster autoscaling.
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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).
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Proven ability to build and maintain self-service developer platforms and golden-path templates on Kubernetes.
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2+ years of experience operating workloads on Cloud platforms (AWS, Azure, or Google Cloud Platform), including networking, IAM, and cost optimisation.
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Strong knowledge of observability: metrics (PrometheGrafana), logging (ELK / OpenSearch), and distributed tracing.
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Experience with service mesh technologies (Istio, Linkerd) and API gateway patterns.
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Solid experience in Agile methodologies (Kanban and SCRUM).
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Strong technical design and analysis skills; ability to deal with ambiguity and work in a fast-paced environment.
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Excellent communication skills, both written and verbal, with strong collaboration skills across multiple teams.
qualifications:
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3+ years of experience developing microservices with Java and Spring Boot.
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Strong understanding of microservices architecture, REST APIs, and event-driven design patterns.
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Experience containerising and deploying Java applications to Kubernetes, including JVM tuning for container environments.
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Familiarity with build tooling (Maven, Gradle) and code quality practices (unit/integration testing, static analysis).