Kafka Platform Engineer (Irvine)THOUGHT BYTE • Irvine, CA, US

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Kafka Platform Engineer (Irvine)

THOUGHT BYTE • Irvine, CA, US

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[job_card.part_time]

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Job Title : Kafka Platform Engineer

Location : Irvine, CA (Hybrid)

Duration : Long Term Contract

Description :

We are seeking a Senior Kafka Engineer to manage, enhance, and scale an enterprise-grade Apache Kafka implementation deployed on AWS and the Confluent Platform.
This person will be responsible for keeping the system reliable, improving it over time, and expanding it to support new applications.
This role involves performing detailed architectural reviews, monitoring, performance tuning, optimizing existing Kafka pipelines, and partnering with application teams to deliver reliable, secure, and performant streaming solutions in a FinTech environment.

Qualifications :

10+ years in platform engineering with 3+ years of hands-on experience with Apache Kafka.

Proficiency in Kafka client development using Java or Python.

Expertise with Confluent Platform (Brokers, Schema Registry, Control Center, ksqlDB).

Experience deploying and managing Kafka on AWS (including MSK or self-managed EC2-based setups).

Solid understanding of Kubernetes, especially EKS, for microservices integration.

Hands-on experience with Kafka Connect, Kafka Streams, and schema management.

Infrastructure automation experience with Terraform and Helm.

Familiarity with monitoring and alerting stacks : Prometheus, Grafana, ELK, or similar.

Preferred Qualifications :

Prior experience in the FinTech domain or other regulated industries.

Understanding of security best practices, including TLS, authentication (SASL, OAuth), RBAC, and encryption at rest.

Exposure to Apache Flink, Spark Streaming, or other stream processing engines.

Experience establishing Kafka governance frameworks and multi-tenant topic strategies.

Must Have & Desired Skills : Confluent Kafka, Terraform, Kubernetes, EKS.

Nice to have Kafka Certification.

Responsibilities :

Manage and enhance existing Apache Kafka and Confluent Platform on AWS.

Review existing implementations and recommend improvements.

Collaborate with engineering and product teams to integrate new use cases and define scalable streaming patterns.

Implement and maintain Kafka producers / consumers, Connectors, and Kafka Streams applications.

Enforce governance around topic design, schema evolution, partitioning, and data retention.

Monitor, troubleshoot, and tune Kafka clusters using Confluent Control Center, Prometheus, and Grafana.

Use Kubernetes and Terraform to automate Kafka infrastructure deployment and scaling.

Ensure high availability, security and disaster recovery.

Mentor other engineers and provide leadership in Kafka-related initiatives.

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