Senior Software Engineer

Confluent Confluent · Data AI · ON +1 · Remote · Engineering

Backend engineers at Confluent build the cloud services and systems that power their data streaming platform. This role focuses on large-scale, distributed backend systems that need to be highly available, reliable, and easy to operate. Responsibilities include designing, building, and operating secure, reliable, and scalable backend services, owning features end-to-end, working with distributed systems and microservices, contributing to service reliability and operations, and collaborating with partner teams. Requires 3+ years of experience in backend systems, distributed systems, cloud deployment, and databases, with a focus on quality and reliability.

What you'd actually do

  1. Design, build, and operate backend services that are secure, reliable, and scalable in a cloud-native environment.
  2. Own features and projects end to end: requirements, design, implementation, testing, rollout, and ongoing improvements.
  3. Work with distributed systems and microservices, with a focus on performance, resiliency, and clear API contracts.
  4. Contribute to service reliability and operations, including monitoring, alerting, and on-call participation where applicable.
  5. Collaborate with partner teams on architecture, data modeling, and integration points across Confluent’s platform.

Skills

Required

  • 3+ years of industry experience designing, building, and supporting backend systems in production.
  • Strong programming and algorithmic skills in at least one major language (for example, Java, Go, C/C++, or Python), and the ability to learn new languages and frameworks as needed.
  • Experience with distributed systems or large-scale backend services, such as microservices, data pipelines, event-driven architectures, or high-throughput APIs.
  • Hands-on experience deploying and operating services on a public cloud (AWS, GCP, or Azure), including knowledge of containers and orchestration tools (for example, Docker and Kubernetes).
  • Familiarity with databases and storage systems, such as relational databases, NoSQL stores, or distributed data systems, and an understanding of performance and scalability tradeoffs.
  • A focus on quality and reliability, including testing strategies, observability (metrics, logging, tracing), and incident response best practices.
  • Strong communication and collaboration skills, with the ability to work effectively with cross-functional partners across time zones.

Nice to have

  • BS, MS, or PhD in computer science, engineering, or a related field, or equivalent practical experience.
  • A growth mindset: you’re curious, open to feedback, and comfortable working in areas that may be new to you.