Kafka Engineer, Kafka ArchitectTechnical/Functional Skills
- Strong fundamentals in distributed systems design and operations, microservice architecture, integration patterns.
- Deep understanding of different messaging paradigms (pub/sub, queuing), as well as delivery models, quality-of-service, and fault-tolerance architectures.
- Established track record with Kafka technology, with hands-on production experience and a deep understanding of the Kafka architecture and internals of how it works, along with interplay of architectural components: brokers, Zookeeper, producers/consumers, Kafka Connect, Kafka Streams.
- Practical experience with how to scale Kafka, KStreams, and Connector infrastructures.
- Experience with Kafka Streams / KSQL architecture and associated clustering model.
- Hands-on experience as a developer who has used the Kafka API to build producer and consumer applications, along with expertise in implementing KStreams components.
- Have developed KStreams pipelines, as well as deployed KStreams clusters.
- Experience with developing KSQL queries and best practices of using KSQL vs KStreams.
- Strong knowledge of the Kafka Connect framework, with experience using several connector types: HTTP REST proxy, JMS, File, SFTP, JDBC.
- Experience using Source/sink connectors asRDBMS, NoSQL data stores.
- Hands-on experience in designing, writing, and operationalizing new Kafka Connectors using the framework.
- Strong familiarity of data formats such as XML, JSON, Avro, CSV, etc. along with serialization/deserialization options.
- Familiarity of the Schema Registry.
- Experience with monitoring Kafka infrastructure along with related components (Connectors, KStreams, and other producer/consumer apps).
- Familiarity with Confluent Control CenterFirm understanding of SDLC (systems development lifecycle).
- Excellent written and verbal communication skills.
- Excellent analytical and troubleshooting abilities.
- Prior experience in banking / financial services industry and firm understanding of the banking data landscape.
Salary Range - $100,000-$130,000 a year#LI-NS2