Home › Companies › Stripe › Staff Software Engineer, Stream Compute
Staff Software Engineer, Stream Compute
Stripe · San Francisco, Seattle, New York, Toronto · Remote · Active · Greenhouse
Job facts
| Field | Value |
|---|---|
| Company | Stripe |
| Title | Staff Software Engineer, Stream Compute |
| Normalized title | - |
| Department / team | 8127 Core Infrastructure |
| Location | United States |
| Work model | Remote / Remote |
| Employment type | - |
| Salary | - |
| Status | active |
| ATS provider | Greenhouse |
| Posted / first seen | 2026-03-31 / 2026-05-29 |
| Changed / last seen | 2026-06-06 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Stripe. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Greenhouse. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Department jobs | Active postings in 8127 Core Infrastructure. | Open |
| Work model jobs | Active Remote postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Stripe |
| Source | f6595d85-f0f8-440c-8dc1-b0386dc838fa |
| ATS provider | Greenhouse |
Description
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.
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 exactly-once processing is supported 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.
What you'll do
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.
Responsibilities
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 and contributing 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.
Minimum requirements
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
Preferred qualifications
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.)
Full job record
| Job ID | 1f50ebcde521302fcb4f5b48c2e54687b72fb358 |
| Org ID | 513d0053-fcfc-4400-8e5b-bd4bd13e8763 |
| Source ID | f6595d85-f0f8-440c-8dc1-b0386dc838fa |
| Board ID | f6595d85-f0f8-440c-8dc1-b0386dc838fa |
| Provider | greenhouse |
| Provider Job Key | 7767063 |
| Title | Staff Software Engineer, Stream Compute |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | San Francisco, Seattle, New York, Toronto |
| Department | 8127 Core Infrastructure |
| Team | — |
| Employment Type | — |
| Workplace Type | remote |
| Remote Policy | remote |
| Country | United States |
| Region | — |
| City | — |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://stripe.com/jobs/search?gh_jid=7767063 |
| Apply URL | https://stripe.com/jobs/search?gh_jid=7767063 |
| First Seen At | 2026-05-29 22:43:12Z |
| Last Seen At | 2026-06-06 07:35:42Z |
| Last Checked At | 2026-06-06 07:35:42Z |
| Last Changed At | 2026-06-06 07:35:42Z |
| Inactive At | — |
| Source Posted At | 2026-03-31 17:59:18Z |
| Source Updated At | 2026-06-05 18:38:49Z |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=stripe/date=2026-06-06/2026-06-06T07-35-41-937Z-ed50622e5b1077bf6f1b14de3e01cb58fd726c22e01084f203cb64f00294e085.json |
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