Role Title : Distributed Cache & DevOps Engineer
Must Have : Hazelcast , Redis / Redis Cluster, Apache Ignite
Role Summary
We are looking for a technically strong Distributed Cache Support Engineer to provide operational, technical, and production support for distributed caching solutions. The ideal candidate should have a strong Java background, prior experience with enterprise caching or in-memory data grid platforms, and hands-on exposure to DevOps and Kubernetes-based environments.
This role requires a hybrid profile combining Java backend engineering, distributed cache troubleshooting, platform operations, performance analysis, and production support.
Key Responsibilities
Cache Platform Support
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Provide L2/L3 support for Distributed Cache clusters and related application integrations.
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Monitor cluster health, member status, partition distribution, memory utilization, latency, and throughput.
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Support cache configuration, including distributed maps, Near Cache, eviction policies, TTL, backup count, serialization, and cluster discovery.
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Troubleshoot cache-related incidents such as high latency, memory pressure, node restarts, split-brain scenarios, data inconsistency, and degraded performance.
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Assist in capacity planning, performance tuning, and operational improvements for environments.
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Coordinate with vendor support teams for product-level issues, patches, upgrades, and escalations.
Java / Application Support
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Analyze Java application behavior related to distributed cache platform integration.
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Troubleshoot JVM-level issues including heap usage, garbage collection, thread dumps, memory leaks, and serialization overhead.
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Work with application teams to identify cache misuse, inefficient access patterns, and performance bottlenecks.
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Support Spring Boot / Java microservices interacting with distributed cache platform.
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Review and validate application-side configurations and integration patterns.
DevOps / Kubernetes Operations
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Support distributed cache platform deployments running on Kubernetes or containerized environments.
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Work with Kubernetes objects such as pods, services, namespaces, configmaps, secrets, deployments, and stateful workloads.
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Analyze pod restarts, resource limits, liveness/readiness probe failures, service discovery issues, and container logs.
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Support configuration management and deployment activities through CI/CD pipelines.
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Assist with TLS/mTLS certificate-related troubleshooting where applicable.
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Work with infrastructure and platform teams on network, DNS, storage, compute, and security-related issues.
Monitoring, Incident & RCA Management
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Monitor platform and application metrics using tools such as AppDynamics, Splunk, Prometheus, Grafana, ELK, or similar.
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Participate in incident management, troubleshooting calls, war-room support, and issue triage.
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Prepare root cause analysis reports for production incidents.
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Recommend preventive actions, operational improvements, and automation opportunities.
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Maintain runbooks, SOPs, known-error documents, and support knowledge base articles.
Required Skills & Experience
Mandatory Skills
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Strong hands-on experience in Java backend development or Java platform support.
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Good understanding of JVM internals, memory management, garbage collection, thread dumps, and heap analysis.
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Prior experience with distributed caching or in-memory data grid solutions.
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Hands-on experience with at least one of the following:
Hazelcast
Redis / Redis Cluster
Apache Ignite
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Experience supporting applications in production or near-production environments.
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Working knowledge of Kubernetes, containers, Linux, and basic networking.
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Ability to analyze logs, metrics, alerts, and application behavior during incidents.
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Strong troubleshooting, communication, and documentation skills.
Preferred Skills
Direct hands-on experience with distributed cache platform & Understanding of:
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Distributed maps
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Near Cache
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Eviction and expiry policies
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Partitioning
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Backup/replication
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Split-brain protection
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Serialization
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Cluster discovery
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Experience with Spring Boot and microservices architecture.
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Experience with CI/CD tools such as Jenkins, GitLab CI, Azure DevOps, or similar.
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Exposure to Anthos, OpenShift, or enterprise Kubernetes platforms.
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Experience with AppDynamics, Splunk, Prometheus, Grafana, ELK, or similar observability tools.
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Knowledge of TLS/mTLS, certificates, service mesh, and secure service communication.
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Experience working in banking, telecom, or other mission-critical enterprise environments.
Minimum Qualification
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Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or equivalent experience.
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5+ years of experience in Java backend development, platform engineering, or production support.
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2+ years of experience with caching, distributed systems, Kubernetes, or DevOps-related operations.
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Prior production support experience in enterprise environments.
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