About the team

The Stream Compute team at Stripe builds and operates the infrastructure, tooling, and systems behind our Flink-powered stream processing systems . We're at the heart of several core asynchronous workflows, operating at significant scale and handling vast amounts of sensitive financial data. Our work powers intricate processes involving various critical financial operations and real-time analytics . We run globally distributed systems with high reliability and performance to meet Stripe's scaling, availability, and product needs, and we continually reduce operational toil by investing in automation and self-service tooling for upgrades, maintenance, and day-to-day operations. The team is distributed between Seattle, Toronto and remote locations.

What makes our team truly exciting is our commitment to our users : we ensure no event is dropped, state integrity is preserved, and support exactly-once processing as a first-class feature. Working at the intersection of real-time data processing and fintech innovation , we continuously push the boundaries of what's possible. Our focus on innovation, user experience, reliability, and compliance drives increased ROI and operational excellence, making us a crucial part of Stripe's success .

You'll help define and deliver the next generation of Stripe's Flink-first stream compute infrastructure—driving innovation to meet extremely high availability targets at global scale. Partnering with infrastructure engineers, adjacent platform teams, and the product orgs that depend on Flink every day, you'll set a long-term technical direction that scales with Stripe's growth while enabling reliable, efficient operations for years to come. You'll work on the hardest problems in operating Flink in production—state management, exactly-once processing, performance isolation, and automated recovery—so teams across Stripe can confidently build stateful stream processing applications on top of it.

• Design, build, and operate stream compute infrastructure with Apache Flink at the center, alongside technologies like Kafka, Temporal, and AWS services
• Partner with product and platform teams across Stripe to understand requirements, unblock Flink adoption, and improve how stream processing infrastructure is used end-to-end
• Define and implement operational best practices (e.g., shuffle sharding, cellular architecture, load shedding, automated state recovery) to improve resilience and reliability at scale
• Drive fleet-level automation and standardization ("pets" to "cattle") through self-service workflows, safer rollouts, and self-healing systems that reduce manual operations
• Lead initiatives that raise the bar on Flink availability and state durability (e.g., multi-region strategies, disaster recovery readiness, operational readiness reviews, incident learning)
• Evaluate and productionize Flink ecosystem capabilities (e.g., SQL, connectors, state backends) to improve developer experience and scalability without compromising reliability
• Work closely with the open source community to identify opportunities for adopting new open source features as well as contribute back to OSS
• Who you are
• We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
• This is a Staff-level role - that typically means 10+ years of experience building, operating, and evolving large-scale production systems
• Experience as a technical lead for team(s) working on distributed systems, including scaling them in fast-moving environments
• Hands-on experience with big data technologies such as Flink, Spark, Kafka, Pulsar, or Pinot
• Experience developing, maintaining and debugging distributed systems built with open source tools
• Experience building and scaling infrastructure as a product
• Strong software engineering skills and a passion for Big Data Distributed Systems
• Ability to write high quality code (in programming languages like Go, Java, Scala, etc)
• Comfortable operating with high autonomy and ownership
• Growth mindset and a willingness to learn quickly, explore ambiguous problem spaces, and dive deep when needed
• Strong written and verbal communication skills, including the ability to produce clear technical documentation
• Experience operating streaming infrastructure as a platform (e.g., Flink clusters, Kafka, Pulsar) for internal customers at scale
• Deep hands-on experience authoring, optimizing, and operating real-time processing frameworks such as Flink, Spark Streaming, Storm, or Kafka Streams in production
• Experience building or operating control planes for managing large-scale infrastructure

Open source contributions to data processing or big data systems (Hadoop, Spark, Celeborn, Flink, etc)