Staff Software Engineer - Data Platform

Checkout

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Kafka and flink stream processing
Event streaming platform development
Cloud-based technologies (aws, kubernetes)
** Checkout.com is seeking a Staff Software Engineer for its Data and AI Platform Team, focusing on building scalable event streaming platforms. The ideal candidate should have strong technical expertise in data systems, particularly with stream processing technologies like Kafka and Flink, and possess excellent leadership and communication skills. **

Job Summary

  • Our team's mission is to build a platform where you can create reliable, scalable, AI-powered streaming and batch data applications, and share data across Checkout.com to improve business performance.
  • The Data and AI Platform team is here to ensure internal stakeholders can easily collect, store, process and utilise data to build AI use cases and data products aiming to solve business problems.
  • We create the conditions for high performers to thrive – through real ownership, fewer blockers, and work that makes a difference from day one.

Matching Summary

Match Score: 75

** Checkout.com is seeking a Staff Software Engineer for its Data and AI Platform Team, focusing on building scalable event streaming platforms. The ideal candidate should have strong technical expertise in data systems, particularly with stream processing technologies like Kafka and Flink, and possess excellent leadership and communication skills. **

Skills & Requirements

Must-have

  • Kafka and Flink stream processing
  • Event streaming platform development
  • Cloud-based technologies (AWS, Kubernetes)
  • Docker and container deployment
  • Infrastructure as code (Terraform)
  • CI/CD pipeline implementation
  • Java, Python, Scala, or C# programming

Nice-to-have

  • Strong presentation and communication skills
  • Proven track record of influencing organizations
  • Experience with Kinesis
  • Experience with SQL databases

Key Requirements

  • Experience implementing and owning event streaming platforms
  • Hands-on experience with stream technologies (Kafka, Kinesis)
  • Experience designing and implementing stream processing applications with Flink
  • Experience with cloud-based technologies (AWS, Kubernetes, Docker)
  • Experience with infrastructure as code (Terraform)
  • Excellent programming skills (Java, Python, Scala, C#)

Work Rights

Not specified

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