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Stripe is seeking a Staff Data Engineer in Toronto to lead a team responsible for building and operating scalable data pipelines and data warehouses. You will collaborate across product and risk teams to enable analytics, ML capabilities, and data-driven decision making across Stripe’s platforms.
The role emphasizes autonomy, a strong backend/data engineering background, and hands-on experience with distributed data tools, while promoting inclusive, high-quality engineering practices.
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.
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.
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.