Software Development Engineer 2

2 hours ago

Chennai, IndiaMid Level / Senior

Responsibilities

Own one or more fault-management modules from low-level design through production support.
Build near-real-time event-driven pipelines with Kafka Streams and Kafka Connect for fault ingestion, correlation, and enrichment.
Implement Apache Spark batch and micro-batch jobs for large-scale fault analytics.
Develop cloud-native Java and Spring Boot microservices with idempotent consumers, dead-letter queues, back-pressure, and delivery semantics.
Integrate ML-powered anomaly detection and root-cause analysis into fault workflows and prototype AI capabilities for automated fault resolution.
Debug Kafka brokers, Streams topologies, Spark executors, and Spring Boot services, serving as the primary escalation point for critical production incidents.
Write runbooks, post-mortems, design documents, and technical decision records.
Contribute to unit, integration, and contract testing, code reviews, observability, on-call support, CI/CD, and infrastructure-as-code improvements.

3–8 years of hands-on backend or data engineering experience.
Production experience with Apache Kafka, including topics, partitioning, consumer groups, and offset management.
Strong knowledge of Kafka Streams DSL and Processor API, including stateful and stateless topologies.
Experience with Kafka Connect source and sink connectors and lifecycle management.
Experience with Apache Spark Structured Streaming, DataFrames, and Spark SQL at scale.
Strong Java 11+ and Spring Boot 3.x experience, including REST, security, and reactive patterns.
Ability to debug complex multithreaded, distributed JVM systems.
Knowledge of low-level and high-level design documentation and distributed-systems principles such as the CAP theorem and eventual consistency.
AIOps or observability platform experience is preferred.
Experience with agentic development workflows or LLM-integrated toolchains is preferred.
Telecom fault-management standards such as TM Forum and IETF YANG/NETCONF, or OSS/BSS domain knowledge, is preferred.
Experience with Kubernetes, service meshes, or AWS, Azure, or GCP cloud-native deployments is preferred.

5,001-10,000 employees