- Страна
- Индия
Откликайтесь
на вакансии с ИИ

Staff Engineer, Data Engineering Solutions
Stripe — один из самых престижных работодателей в финтехе с высочайшей инженерной культурой. Позиция предлагает работу с современным стеком (Iceberg, Trino, AI) и возможность влиять на глобальную финансовую инфраструктуру.
Сложность вакансии
Роль уровня Staff требует более 10 лет опыта и глубоких знаний в распределенных системах (Spark, Flink, Kafka). Высокая сложность обусловлена необходимостью совмещать глубокую техническую экспертизу с лидерством и кросс-функциональным взаимодействием в условиях высокой неопределенности.
Анализ зарплаты
Для позиции Staff Engineer в Бангалоре Stripe обычно предлагает зарплату в верхнем дециле рынка, дополненную значительным пакетом акций (RSU). Указанный рыночный диапазон отражает уровень топовых технологических компаний (Tier-1) в данном регионе.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Engineer, Data Engineering Solutions position at Stripe. With over 10 years of engineering experience and a deep specialization in building large-scale data systems using Spark, Kafka, and Airflow, I have consistently delivered robust data architectures that handle billions of events. My background in both backend development and data warehousing aligns perfectly with Stripe's mission to provide trustworthy, cost-effective data infrastructure.
Throughout my career, I have led technical teams to solve complex data quality issues and have a proven track record of collaborating with product teams to build canonical datasets. I am particularly excited about Stripe's focus on leveraging AI/LLM and Agents at scale to enhance data operations. I am confident that my expertise in distributed frameworks and my commitment to fostering an inclusive, high-performing engineering culture will allow me to make a significant impact on your Data Foundations team in Bengaluru.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в stripe уже сейчас
Присоединяйтесь к Stripe, чтобы определять будущее финансовых данных в глобальном масштабе и работать с передовыми AI-технологиями.
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
We are experts in data, working to make it cost-effective, understandable, and trustworthy. We build pipelines processing billions of events a day and are stewards of canonical data warehouses and datasets delivering products for Stripe Users while embedding with teams to build their data products. We are experts in using the Stripe Data Platform and to scale we lead the data culture and data education to enable product teams to own their data. We invest in [AI] Data Ops to scale incident handling and serve as an escalation path for data incidents to minimize their impact. The Data Engineering Solutions team will work closely with product teams delivering trustworthy data / backend code / and innovative (AI) tools/platforms/services for data.
What you’ll do
We're looking for a person who could drive the Data Engineering Solutions Team in solving high-impact, cutting-edge data problems. The ideal candidate will be someone that has built data pipelines for large scale volume, is deeply knowledgeable of Data Engineering tools including Airflow/Spark/Kafka/Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities.
You will:
- Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success.
- Partner with our recruiting team to attract and hire top talent.
- Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency.
- Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders.
- Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data.
- Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems
- Have an opportunity to work with Spark, Flink, Kafka, Trino, Pinot, Airflow, Scala, Java, SQL, and Python and many other big data technologies.
- Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion.
- Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team.
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
We’re looking for someone who has:
- 10+ Years of engineering experience with5+ Years of hands-on experience building+operating data systems/pipelines, datasets/data warehouses, infrastructure, and leading small teams to deliver exceptional solutions.
- A strong engineering background and passion for data.
- Prior experience with writing and debugging data pipelines using a distributed data framework (Spark / Hadoop / Trino / etc)
- An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
- Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience
- Extreme customer focus, with a commitment to partnering with Product Managers, leaders, and other Stripe engineers to understand their use cases.
- Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs.
- Thrive with high autonomy and responsibility in an ambiguous environment.
- Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment.
Preferred qualifications
- Expertise in Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, AWS Cloud, and influencing open-source contributions is a plus.
- Experience creating and maintaining Data Marts / Data Warehouses to power business reporting needs
- Experience working with Product or Go-To-Market (GTM - Sales/Marketing) teams
- Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions.
- Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide.
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- AWS
- Python
- SQL
- Airflow
- Kafka
- Hadoop
- Java
- Spark
- Flink
- Go
- Scala
- Change Data Capture
- Iceberg
- Trino
- Pinot
Возможные вопросы на собеседовании
Для уровня Staff критически важно понимать, как архитектурные решения влияют на стоимость и производительность при обработке миллиардов событий.
Расскажите о самом сложном случае оптимизации производительности или стоимости в вашей практике проектирования пайплайнов данных. Каких компромиссов пришлось достичь?
Вакансия предполагает работу с AI/LLM для масштабирования Data Ops. Проверяется готовность кандидата к инновациям.
Как бы вы спроектировали систему на базе LLM-агентов для автоматического обнаружения и устранения инцидентов в качестве данных в масштабах Stripe?
Роль требует лидерства без прямого административного подчинения и влияния на другие команды.
Опишите ситуацию, когда вам нужно было убедить другую команду изменить их подход к владению данными или архитектуре. Как вы выстраивали аргументацию?
Stripe делает упор на надежность и SLA. Проверяется опыт эксплуатации критических систем.
Как вы подходите к обеспечению отказоустойчивости и соблюдению SLA в системах потоковой обработки данных (например, Flink или Kafka)?
Вакансия упоминает создание канонических хранилищ данных. Проверяется знание методологии моделирования.
Каковы ваши принципы проектирования канонических витрин данных (Data Marts), которые должны одновременно служить множеству различных продуктовых команд?
Похожие вакансии
MLOps Engineer
Инженер Mlops (Senior)
Middle+ ML разработчик
Senior MLOps Engineer (Platform Development / LLMOps)
Data engineer
Senior Data Engineer
1000+ офферов получено
Устали искать работу? Мы найдём её за вас
Quick Offer улучшит ваше резюме, подберёт лучшие вакансии и откликнется за вас. Результат — в 3 раза больше приглашений на собеседования и никакой рутины!
- Страна
- Индия