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Staff Software Engineer, Stream Compute
Stripe — один из лучших работодателей в финтехе с уникальными инженерными задачами. Позиция предлагает высокую степень автономности, работу с передовым стеком (Flink, Kafka) и возможность влиять на глобальную финансовую инфраструктуру.
Сложность вакансии
Роль уровня Staff требует более 10 лет опыта и глубоких знаний в области распределенных систем и Apache Flink. Высокая сложность обусловлена необходимостью решать задачи масштабирования и надежности для критически важных финансовых данных.
Анализ зарплаты
Указанная роль Staff-уровня в Stripe обычно предполагает компенсацию выше среднерыночной, включая значительную долю в виде акций (RSU). В крупных технологических хабах США и Канады такие позиции оцениваются в верхнем дециле рынка.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Software Engineer position within the Stream Compute team at Stripe. With over a decade of experience in building and evolving large-scale distributed systems, I have developed a deep expertise in Apache Flink and Kafka, which aligns perfectly with Stripe's mission to provide robust financial infrastructure. My background includes leading technical initiatives that prioritize state integrity and exactly-once processing, ensuring that critical financial data is handled with the highest level of reliability.
In my previous roles, I have successfully driven the transition from manual operations to automated, self-healing systems, significantly reducing operational toil. I am particularly drawn to Stripe's commitment to innovation and its 'Flink-first' approach to infrastructure. I am eager to bring my experience in multi-region strategies and disaster recovery to help scale Stripe's stream processing capabilities while maintaining the high availability targets that your global users depend on.
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Описание вакансии
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 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.
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 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.
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)
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Навыки
- AWS
- Apache Spark
- Distributed Systems
- Java
- Apache Flink
- Big Data
- Temporal
- Apache Kafka
- Go
- Scala
Возможные вопросы на собеседовании
Проверка глубокого понимания внутреннего устройства Flink для обеспечения надежности данных.
Как бы вы реализовали семантику exactly-once в распределенной системе с использованием Flink и Kafka, и какие потенциальные узкие места вы видите?
Оценка опыта проектирования отказоустойчивых систем.
Опишите ваш подход к проектированию стратегии аварийного восстановления (Disaster Recovery) для крупномасштабного кластера Flink с сохранением состояния.
Проверка навыков оптимизации производительности.
С какими проблемами производительности при управлении состоянием (state management) во Flink вы сталкивались и как их решали?
Оценка лидерских качеств и умения работать с инфраструктурой как с продуктом.
Как вы балансируете между внедрением новых функций из open-source сообщества и поддержанием стабильности внутренней платформы для других команд?
Проверка архитектурного мышления.
Как бы вы внедрили концепцию 'cellular architecture' для стриминговой инфраструктуры Stripe, чтобы минимизировать радиус поражения при сбоях?
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