Note: The job is a remote job and is open to candidates in USA. Verri is seeking a Senior Software Engineer with expertise in cloud-based Kafka and large-scale distributed systems. The role involves designing, building, and operating high-throughput, low-latency streaming services, while ensuring the reliability and performance of Kafka-centric data infrastructure in AWS and/or Azure.
Responsibilities
- Architect, build, and operate Kafka clusters in cloud environments (AWS MSK, Azure Event Hubs for Kafka, Confluent Cloud, or self-managed)
- Design topic strategies, partitioning schemes, retention policies, and replication models for high-scale workloads
- Implement schema governance, compatibility workflows, and event-driven design patterns
- Design the Kafka messaging backbone that connects various internal and external gateways, notification engine and user profiles
- Build idempotent consumers to ensure that an event is processed exactly once across all services
- Build fault-tolerant, horizontally scalable services using modern languages (Java, Go, Rust, or C#)
- Develop streaming pipelines and real-time processing components using Kafka Streams, Flink, Spark Structured Streaming, or equivalent frameworks
- Own end-to-end system design, including data contracts, SLAs/SLOs, observability, and operational readiness
- Design and optimize multi-cloud or hybrid architectures for data streaming systems
- Implement monitoring, alerting, and distributed tracing for Kafka and dependent services
- Drive incident response, root-cause analysis, and long-term reliability improvements
Skills
- 8+ years of software engineering experience which includes building backend or distributed systems and 3+ years of hands-on experience with Apache Kafka
- Deep hands‑on experience with Kafka (producers, consumers, brokers, partitions, replication, consumer groups)
- Strong programming skills in Java, Go, Rust, or C#
- Experience designing and operating large‑scale distributed systems in cloud environments
- Familiarity with streaming frameworks (Kafka Streams, Flink, Spark) and distributed storage systems (Cassandra, Redis, Elasticsearch)
- Strong understanding of networking, consensus, replication, and distributed system fundamentals
- Experience deploying and operating Kafka in AWS, Azure, or multi‑cloud environments
- Familiarity with Kubernetes, Helm, and cloud‑native deployment patterns
- Experience with CI/CD pipelines, observability stacks, and infrastructure automation
- Excellent communication and cross‑team collaboration skills
- Ability to lead technical initiatives and drive architectural clarity
- Strong debugging, performance tuning, and systems‑thinking mindset
- Experience with Confluent Platform or Managed Kafka services
- Experience building high‑durability, low‑latency systems
- Experience with large‑scale data infrastructure or analytics platforms
Company Overview