Kafka Platform Engineer

Bright Vision Technologies•Apex, MO

4d•$130,000 - $180,000•Remote

About The Position

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.

Requirements

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, OpenTelemetry, ELK, and distributed tracing solutions.
Excellent troubleshooting, communication, documentation, stakeholder management, and technical leadership skills.

Nice To Haves

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.

Responsibilities

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, OpenTelemetry, 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, DevOps, 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.