We’re not just building better tech. We’re rewriting how data moves and what the world can do with it. With Confluent, data doesn’t sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them.

It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together.

One Confluent. One Team. One Data Streaming Platform.

About the Role:

We are a team of passionate engineers who love solving complex distributed storage systems and infrastructure problems. Through the Tableflow project, we are building the next generation of storage solutions for Kora, transforming it into a true multi-modal storage engine. Our goal is to enable streaming data to be consumed both as a table and as a stream seamlessly. If you're interested in learning more about the challenges we are tackling, check out our blog post: Tableflow: The Stream/Table, Kafka/Iceberg Duality.

As a Staff Software Engineer on the team, you will focus on advancing key layers of the Tableflow project, including its multi-tenant, highly available compute infrastructure, and the core components responsible for table materialization and background maintenance. You will tackle challenges such as developing strategies for efficient table materialization and maintenance at massive scale across all of Confluent Cloud, ensuring high availability and scalability for background storage tasks.

What You Will Do:

• Storage Engine Development: Design and implement innovative strategies for table schematization, materialization, and compaction at massive scale.

• Platform Engineering: Build and maintain multi-tenant, highly available infrastructure that powers background computational tasks for Kora’s long-term storage. Ensure that the platform is optimized for scalability, reliability, and resilience, in alignment with organizational objectives.

• Open-Source Leadership: Guide and mentor team members in contributing to relevant open-source projects such as Apache Iceberg. Advocate for best practices in open-source collaboration and foster a culture of giving back to the community.

• Engineering Leadership: As a staff engineer, set the standard for engineering excellence. Act as a trusted advisor for both internal and cross-functional teams, providing guidance on complex technical problems and contributing to high-level decision-making processes.

• Cross-Functional Collaboration: Collaborate with product management, design, and other engineering teams to ensure seamless integration of storage features and infrastructure with the broader organization.

What You Will Bring:

• BS, MS, or PhD in computer science or a related field, or equivalent work experience

• Proven experience designing and building large-scale, distributed storage systems.

• Deep knowledge of distributed systems concepts, including fault tolerance, consistency, and scalability.

• Expertise in modern cloud-based infrastructure and multi-tenant environments.

• Strong leadership skills with a demonstrated ability to mentor and guide engineers to success.

• Excellent communication and collaboration skills, with the ability to influence and guide stakeholders at all levels.

What Gives You an Edge:

• Familiarity with or has experience contributing to the following open-source technologies: Apache Kafka, Apache Iceberg, Apache Flink

• Experience/knowledge with public clouds (AWS, Azure or GCP)

• Interest in evangelism (giving talks at tech conferences, writing blog posts evangelizing your work)

Ready to build what's next? Let’s get in motion.

Come As You Are

Belonging isn’t a perk here. It’s the baseline. We work across time zones and backgrounds, knowing the best ideas come from different perspectives. And we make space for everyone to lead, grow, and challenge what’s possible.

We’re proud to be an equal opportunity workplace. Employment decisions are based on job-related criteria, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by law.