Key Responsibilities:

Architectural Design & Strategy:

Design end-to-end Kafka-based event streaming architectures for high-throughput, low-latency environments.
Define architectural standards, best practices, reusable patterns, schemas, and governance models.
Enable event-driven architecture (EDA) adoption across platforms and business units.
Develop data modelling standards for events, Avro/JSON schemas, serialization formats, and schema evolution strategies.
Implement enterprise-grade security: ACLs, RBAC, encryption, network segmentation, auditing, and compliance.
Implement disaster recovery frameworks in seamless manner.

Platform Engineering & Implementation

Architect and oversee deployment of self-managed Kafka clusters.
Lead capacity planning, cluster sizing, replication, partitioning strategies, high availability, and disaster recovery.
Implement Kafka Connect and ksqlDB Spark streaming pipelines.

Cross-Functional Leadership

Collaborate with engineering, DevOps, cloud, data, and application teams to drive Kafka architecture adoption.
Provide mentoring and technical leadership to engineering teams on Kafka patterns and anti-patterns.
Review solution architectures, ensure alignment with enterprise standards, and participate in architecture governance boards.

Technical Expertise:

6+ years of hands-on experience with Apache Kafka, Confluent Platform, Schema Registry & Kafka Connect.
Strong knowledge of event-driven architecture, pub/sub messaging, stream processing, and distributed systems.
Experience with stream processing frameworks: Kafka Streams, Spark Structured Streaming, or ksqlDB.
Strong understanding of DevOps and automation tools: Kubernetes, Terraform, Helm, Ansible, Jenkins, GitHub Actions.
Expertise in cloud platforms (AWS/Azure/GCP) for deploying Kafka or managed services.
Proficiency in languages such as Java, Scala, Python, or Go.
Strong knowledge on Kubernetes and helm
Monitoring and observability frameworks like Prometheus and Grafana

Kafka Cloud Engineer