Cloud Engineer-- AGADC

Primary Requirements — Kubernetes & Dev Ops (Must Have)

• Bachelor’s or Master’s Degree in a technology‑related field (e.g. Engineering, Computer Science, etc.) required.
• 5+ 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 Dev Ops practices and tooling: CI/CD pipelines (Jenkins, Git Hub Actions, ArgoCD / Flux Git Ops), 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 GCP), including networking, IAM, and cost optimisation.
• Strong knowledge of observability: metrics (Prometheus/Grafana), logging (ELK / Open Search), 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).

• 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.