General Summary:

The Sr. Streaming Solution Engineer is responsible for designing, implementing and optimizing enterprise-scale real-time data streaming solutions using Apache Kafka and the Confluent Platform. The role focuses on building scalable event-driven architectures, developing advanced streaming applications and ensuring reliable operation of distributed streaming platforms.

Skill Combination:

- Java + Kafka: Strong experience in Kafka Streams, event-driven microservices development, custom connector development, advanced streaming application design, connector configuration, and KSQLDB/Flink query development.

- OR DevOps + Kafka: Strong experience in Kafka platform deployment and operations, cluster architecture design, infrastructure automation (Terraform / Ansible), CI/CD pipeline implementation, monitoring, and performance optimization of streaming platforms.

Key Responsibilities:

- Design and implement enterprise-scale real-time streaming architectures using Apache Kafka and the Confluent Platform.

- Lead the development of Kafka-based streaming applications, event-driven microservices and integration pipelines.

- Design and implement high-throughput, fault-tolerant streaming data pipelines across enterprise systems.

- Develop and optimize Kafka producers, consumers and streaming services to ensure reliable and efficient data flow.

- Define topic design, partition strategies, replication policies, and consumer group scaling models.

- Design and implement Kafka Connect integrations including development of custom connectors when required.

- Leverage KSQLDB or Apache Flink for real-time data transformations, filtering, and aggregations.

- Lead performance tuning, troubleshooting and optimization of Kafka clusters and streaming workloads.

- Collaborate with DevOps teams to implement CI/CD pipelines, infrastructure automation and containerized deployments.

Required Skills & Qualifications:

- 6 - 8 years of relevant experience in software development, data streaming platforms or distributed systems engineering.

- Strong hands-on experience with Apache Kafka or Confluent Platform in enterprise environments.

- Experience designing and implementing event-driven architectures and real-time data streaming pipelines.

- Strong analytical and troubleshooting skills for diagnosing complex distributed system issues.

- Experience working in Linux environments and containerized infrastructures.

Preferred Certifications:

- Confluent Certified Developer for Apache Kafka (CCDAK)

- Cloud platform certifications such as AWS, Azure or Google Cloud

- DevOps-related certifications in Kubernetes, Docker or CI/CD technologies.