The Kora Background Plane team aims to build the best experience for Confluent’s cloud-native Kafka service.
As a Staff Software Engineer, you will design and build efficient and performant algorithms for right sizing, load balancing, and seamless scalability of Kora.
You will provide technical leadership, mentoring, and enable a high-performing engineering team to tackle complex distributed data challenges at scale.
You will build the software underpinning the mission-critical Kora Background Plane platform, focusing on high performance, scalability, reliability, and resilience.
You will collaborate effectively across engineering, product, field teams, and other key stakeholders to create and execute an impactful roadmap for the Kora Background Plane team.
You will meet and exceed Service Level Agreements (SLAs) for critical cloud services owned by the Kora Background Plane team.
You will evaluate and enhance the efficiency of the platform's technology stack, keeping pace with industry trends and adopting state-of-the-art solutions.
Requirements:
You must have 12+ years of relevant software development experience.
You should have 5+ years of experience with designing, building, and scaling distributed systems.
You need deep technical expertise in large-scale distributed systems.
You must have experience running production services in the cloud with demonstrated operational excellence.
Proficiency in Java and Scala is required.
You should have the ability to influence the team, peers, and management using effective communication and collaborative techniques.
Proven experience in leading and mentoring technical teams is necessary.
A BS, MS, or PhD in computer science or a related field, or equivalent work experience is required.
Benefits:
The company promotes a culture of belonging, ensuring that diverse perspectives are valued and everyone has the opportunity to lead, grow, and challenge what’s possible.
Confluent is proud to be an equal opportunity workplace, with employment decisions based on job-related criteria without regard to protected classifications.