Staff Software Engineer, Product Risk

Who we areAbout StripeStripe 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 teamProduct and Risk Data Engineering is Stripe's single source of truth data engineering layer for Payments, Risk, and Product — we enable Stripe to confidently run, measure, and grow the business by making accurate information easy to access. We curate and maintain high-quality data warehouses and pipelines that serve as the authoritative foundation for product and financial activity across Stripe, powering analytics, ML capabilities, agentic workflows, and merchant-facing data interfaces. Beyond building data, we act as the internal experts in data technologies and partner with Data Platform to deliver high-quality, low-friction data processing frameworks. We also serve as the bridge between data producers and data consumers — championing best-in-class data engineering practices and guiding product teams on event-driven data API modeling — so that every team at Stripe can build, decide, and grow from a trusted, well-engineered data foundation.
What you’ll doWe're looking for a person who could contribute to the team by 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 key 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.
Responsibilities
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 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 areWe’re looking for someone who meets the minimum requirements to be considered for the role.
Minimum requirements
This is a Staff-level role — that typically means 10+ years of experience building and operating data systems, pipelines, warehouses, infrastructure, and leading teams to deliver exceptional solutions
A strong engineering background and passion for data as well as prior experience with writing and debugging data pipelines using a distributed data framework
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, leaders across the business, 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 autonom
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