Debugging & Incident Support
Diagnose issues across Kafka brokers, Streams topologies, Spark executors, and Spring Boot services
Primary escalation point for critical production incidents in your module
Write runbooks and post-mortems to prevent repeat incidents
Quality & Operational Excellence
Unit, integration, and contract tests; peer code reviews
Observability — metrics, tracing, structured logging; on-call rotation
Contribute to CI/CD and infra-as-code improvements
Required Skills
6+ years of hands-on backend / data engineering experience
Production Kafka systems — topics, partitioning, consumer groups, offset management
Kafka Streams DSL and Processor API; stateful and stateless topologies
Kafka Connect — source and sink connectors, lifecycle management
Apache Spark — Structured Streaming, DataFrames, Spark SQL at scale
Java 11+ and Spring Boot 3.x — REST, security, reactive patterns
Deep debugging across multi-threaded, distributed JVM systems
LLD/HLD documentation; distributed systems principles (CAP theorem, eventual consistency)
Good to Have
AIOps or observability platform experience
Agentic development workflows or LLM-integrated toolchains
Telecom fault management standards (TM Forum, IETF YANG/NETCONF) or OSS/BSS domain knowledge
Kubernetes, service meshes, cloud-native deployments (AWS / Azure / GCP)
Pre-Requisites / Skills / Experience Requirements
