Senior Software Engineer
Kyndryl
- Location
- Bangalore Karnataka India
- Work model
- On-Site
- Level
- Senior
- Posted
- Aug 19, 2026
Skills
About this role
Who We Are
At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive.
The Role
Role Summary A Senior Kafka Operations Engineer is responsible for ensuring the stability, performance, and reliability of Kafka-based data streaming platforms in production. The role focuses on end-to-end operational support, advanced troubleshooting, and enabling development teams to build resilient, high-performing Kafka integrations. This is a hands-on operational role, working in a 24/7 support environment, with deep involvement in Kafka clients, cluster health, and real-time incident resolution.
What You Will Do
Own production support for Kafka environments in a 24/7 on-call rotation Monitor and maintain Kafka cluster performance, availability, and reliability Perform advanced troubleshooting across the full Kafka stack: Producers, consumers, brokers, and clusters Analyze logs and metrics to proactively detect and resolve issues Ensure minimal downtime and uninterrupted data flow Deep-Dive Troubleshooting Areas Kafka Clients Producer delivery failures, retries, idempotence, acknowledgments Consumer lag, offset issues, delivery guarantees Connectivity & Security TLS handshake failures SASL authentication issues Schema & Serialization Schema compatibility problems Serializer/deserializer failures Performance Slow producers/consumers Throughput bottlenecks (e.g., compression, batching) Cluster Health Partition hot spots Broker performance issues Replication/reliability concerns Collaboration & Impact Support and guide development teams on Kafka best practices Help onboard applications onto Kafka Act as a subject matter expert during incidents and root cause analysis Improve system resilience and operational efficiency What Makes This a Senior Role Deep understanding of distributed systems and Kafka internals Ability to troubleshoot complex, multi-layer issues under pressure Strong communication with both engineering and non-engineering teams Ownership of business-critical production environments Who You Are Role Summary A Senior Kafka Operations Engineer is responsible for ensuring the stability, performance, and reliability of Kafka-based data streaming platforms in production. The role focuses on end-to-end operational support, advanced troubleshooting, and enabling development teams to build resilient, high-performing Kafka integrations. This is a hands-on operational role, working in a 24/7 support environment, with deep involvement in Kafka clients, cluster health, and real-time incident resolution.
What You Will Do
Own production support for Kafka environments in a 24/7 on-call rotation Monitor and maintain Kafka cluster performance, availability, and reliability Perform advanced troubleshooting across the full Kafka stack: Producers, consumers, brokers, and clusters Analyze logs and metrics to proactively detect and resolve issues Ensure minimal downtime and uninterrupted data flow Deep-Dive Troubleshooting Areas Kafka Clients Producer delivery failures, retries, idempotence, acknowledgments Consumer lag, offset issues, delivery guarantees Connectivity & Security TLS handshake failures SASL authentication issues Schema & Serialization Schema compatibility problems Serializer/deserializer failures Performance Slow producers/consumers Throughput bottlenecks (e.g., compression, batching) Cluster Health Partition hot spots Broker performance issues Replication/reliability concerns Collaboration & Impact Support and guide development teams on Kafka best practices Help onboard