Kafka Platform Engineer

Kafka Platform Engineer

Bright Vision Technologies is seeking a highly experienced Kafka Platform Engineer with 10+ years of experience in distributed systems, event streaming, and platform engineering, including extensive expertise with Apache Kafka and the Confluent Platform. The ideal candidate will architect, deploy, and manage enterprise-scale streaming platforms that power mission-critical, real-time data processing across the organization. This role requires deep technical expertise in Kafka internals, platform automation, security, observability, and cloud-native infrastructure, along with the ability to mentor engineering teams and define enterprise event-streaming standards.

• Architect, deploy, and manage highly available Apache Kafka and Confluent Platform environments supporting enterprise-scale event-driven applications.
• Design Kafka cluster topology, broker configuration, partitioning strategies, replication, capacity planning, and performance optimization for high-throughput workloads.
• Implement enterprise-grade security using SASL, SSL/mTLS, ACLs, RBAC, encryption, and authentication mechanisms.
• Design and manage Kafka Connect, Schema Registry, Kafka Streams, ksqlDB, and event streaming pipelines for real-time data integration.
• Develop and maintain Infrastructure as Code using Terraform, Ansible, or similar automation frameworks to provision and manage Kafka infrastructure.
• Design and implement High Availability (HA), Disaster Recovery (DR), backup, failover, and cross-region replication strategies.
• Build comprehensive monitoring, alerting, logging, and observability solutions using Prometheus, Grafana, Open Telemetry, ELK, and Confluent monitoring tools.
• Optimize cluster performance, troubleshoot production issues, conduct root cause analysis, and implement long-term platform improvements.
• Support Kafka deployments on Kubernetes using Strimzi, Confluent Operator, or managed cloud services including AWS MSK, Azure Event Hubs (Kafka API), and Confluent Cloud.
• Collaborate with application developers, data engineers, Dev Ops, SRE, and enterprise architects to establish event-driven architecture standards and best practices.
• Conduct architecture reviews, establish platform governance, perform code reviews, and mentor engineers on Kafka development and operations.

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related technical discipline.
• 10+ years of professional experience in distributed systems, platform engineering, or infrastructure engineering, including 5+ years of hands-on Apache Kafka or Confluent Platform experience.
• Expert-level knowledge of Kafka internals, including partitions, replication, brokers, ISR, consumer groups, offset management, and performance tuning.
• Extensive experience implementing Kafka security using SASL, SSL/mTLS, ACLs, RBAC, and enterprise authentication mechanisms.
• Strong hands-on experience with Kafka Connect, Schema Registry, Kafka Streams, ksqlDB, and real-time event streaming architectures.
• Experience implementing High Availability (HA), Disaster Recovery (DR), multi-cluster replication, and cross-region failover strategies.
• Advanced scripting skills using Python, Bash, or Go, along with Infrastructure as Code experience using Terraform, Ansible, or similar tools.
• Strong experience with observability platforms including Prometheus, Grafana, Open Telemetry, ELK, and distributed tracing solutions.
• Excellent troubleshooting, communication, documentation, stakeholder management, and technical leadership skills.

• Confluent Certified Administrator or Confluent Certified Developer certification.
• Experience operating Kafka on Kubernetes using Strimzi, Confluent Operator, or similar operators.
• Hands-on experience with managed Kafka services including AWS MSK, Confluent Cloud, Azure Event Hubs (Kafka API), or Google Cloud Managed Kafka.
• Experience with stream processing technologies such as Apache Flink, Apache Spark Structured Streaming, or Apache Beam.
• Knowledge of data governance, schema evolution, metadata management, and data lineage for streaming platforms.