Experience -10 years
Job type -full time
Location -remote
Technical/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.
