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. Product 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.

We'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. Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success 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 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 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 robust 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 Our stack is made up of Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, and AWS Cloud - experience with all or some of these tools is a huge plus Experience creating and maintaining data marts / warehouses to power business reporting needs Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions This role is available either in an office or a remote location (35+ miles or 56+ km from a Stripe office). In-office expectations Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users.

Working remotely at Stripe A remote location is defined as being 35 miles (56 kilometers) or more from one of our offices. While you would be welcome to come into the office for team/business meetings, on-sites, meet-ups, and events, our expectation is you would regularly work from home rather than a Stripe office. Stripe does not cover the cost of relocating to a remote location.

For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; medical, dental, and vision benefits; Please find our California applicant personal information notice here.

Data Platform

Office locations Remote locations Remote in Canada, Remote in United States Full time #

📌 Staff Software Engineer, Risk Data Engineering (Toronto)
🏢 Monograph
📍 Toronto