Confluent Integration Engineer

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Key Responsibilities

- Design, develop, and maintain Kafka-based data integration pipelines using Confluent Platform / Confluent Cloud

- Migrate existing custom connectors to Confluent Managed Connectors (S3 Sink/Source, JDBC, Debezium, REST, etc.)

- Configure, deploy, and monitor Kafka Connect clusters and connector instances

- Implement Schema Registry governance (Avro, JSON Schema, Protobuf) for data contracts

- Build and optimise Kafka Streams or ksqlDB applications for real-time data transformation

- Collaborate with the EIDH architecture team on integration patterns (event-driven, CDC, batch offload)

- Troubleshoot connector failures, consumer lag, partition rebalancing, and throughput issues

- Implement observability: monitoring, alerting, and dashboarding for Kafka ecosystem components

- Support data governance, lineage, and security (ACLs, RBAC, encryption in transit/at rest)

- Participate in incident response and production support for streaming infrastructure

Must Have

- 3+ years hands-on experience with Apache Kafka / Confluent Platform / Confluent Cloud

- Strong experience with Kafka Connect — deploying, configuring, and managing connectors (both self-managed and Confluent Managed)

- Experience migrating from custom/self-managed connectors to Confluent Managed Connectors

- Proficiency with Schema Registry and schema evolution strategies

- Experience with at least 3 of the following connectors: S3 Sink/Source, JDBC Source/Sink, Debezium CDC, HTTP/REST Source/Sink, Oracle CDC

- Solid understanding of Kafka internals: partitioning, replication, consumer groups, offset management

- Experience with Infrastructure as Code (Terraform, Ansible) for Kafka/Confluent resource provisioning

- Proficiency in at least one of: Java, Python, or Go for custom connector development or Kafka Streams