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Job Title: Confluent Kafka Tech Lead
Location: Remote / Onsite (As per project requirement)
Experience: 7+ Years
Employment Type: Full-Time
We are seeking a highly skilled Confluent Kafka Tech Lead with deep expertise in designing, implementing, and managing real-time data streaming solutions. The ideal candidate will lead Kafka-based architecture design, ensure best practices, and guide the development and operations teams in implementing scalable, resilient event-driven systems.
Lead the design and architecture of end-to-end event streaming platforms using Confluent Kafka.
Define data streaming patterns, event models, schema registry usage, and partitioning strategies.
Drive adoption of Kafka-centric event-driven architectures across teams.
Guide the development of Kafka producers and consumers using Java/Python.
Implement Confluent features including KSQL, Connect, REST Proxy, Schema Registry.
Oversee integration of Kafka with cloud platforms (Azure/AWS/GCP).
Ensure high availability, scalability, and resiliency of Kafka clusters.
Optimize throughput, partitions, replication, and retention settings.
Implement monitoring, alerting, and logging frameworks.
Provide technical leadership to developers and DevOps teams.
Conduct design reviews, code reviews, and mentor junior engineers.
Work closely with Data Engineering, Platform, and Enterprise Architecture teams.
Define Kafka security standards (ACLs, RBAC, encryption, certificates).
Ensure compliance with data governance and regulatory requirements.
6–7 years of overall IT experience with 4+ years in Confluent Kafka.
Strong experience in Kafka architecture, cluster setup, design, and optimization.
Expertise in Kafka Connect, Schema Registry, KSQL, and Kafka Streams.
Strong programming experience in Java or Python.
Experience with cloud (AWS/Azure/GCP) and containerization (Kubernetes/Docker).
Understanding of event-driven architecture and distributed systems.
Excellent leadership, communication, and problem-solving capabilities.
Confluent Kafka Certification.
Experience in large-scale, high-throughput real-time systems.
CI/CD experience for streaming applications.
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