Stripe is hiring a Staff Software Engineer in Toronto!
Stripe is hiring a Staff Software Engineer for its Product and Risk Data Engineering team in Toronto. This group owns the authoritative data layer behind Payments, Risk, and Product, maintaining warehouses and pipelines that feed analytics, machine learning, agentic workflows, and merchant-facing data products. The role blends hands-on data engineering with technical leadership: you would set direction for a team of engineers, mentor and grow them, help recruit new colleagues, and build reliable, efficient pipelines that hold up at scale. The team also acts as Stripe's in-house authority on data tooling and as the link between teams producing data and teams consuming it, so the position calls for someone who can influence architecture and engineering practice well beyond their own code. Expect to work on ambiguous, high-impact problems, apply LLM- and agent-based approaches at scale, and drive major data initiatives end to end. Stripe emphasizes customer focus, clear communication, and a healthy, inclusive team culture.
Key responsibilities
- Lead the technical outcomes of a team of engineers through mentorship, guidance, and support
- Partner with recruiting to attract and hire strong engineers
- Build and ship data pipelines that scale, with emphasis on reliability and efficiency
- Develop deep subject-matter expertise and manage SLAs for pipelines and supporting full-stack web applications
- Work with product managers and peers across Stripe to improve canonical datasets and warehouses and promote trustworthy data use
- Apply AI, LLM, and agent systems at scale to generate and analyze high-quality data on ambiguous problems
- Own delivery of key data initiatives from planning through launch while maintaining quality and timelines
- Foster an inclusive, collaborative environment that encourages knowledge sharing and continuous improvement
Key requirements
- Staff-level scope, typically 10+ years building and operating data systems, pipelines, warehouses, and infrastructure while leading teams
- Strong engineering background with hands-on experience writing and debugging distributed data pipelines
- Ability to investigate data inconsistencies and resolve deep-rooted data quality problems
- Proficiency in a backend language such as Scala, Java, or Go, plus strong SQL
- Strong customer focus and comfort partnering with product, business leaders, and other engineers
- Effective cross-functional collaboration, rigorous thinking, and clear communication of trade-offs
- Comfort operating with high autonomy in ambiguous environments
- Commitment to a healthy, inclusive, and supportive workplace
- Preferred: experience with Iceberg, Kafka, CDC, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, or AWS
- Preferred: open-source contributions, data mart or warehouse experience, and work with go-to-market teams
- Seniority: Staff-level (10+ years)
- Work mode: Not specified
- Key skills: Scala, Java, Go, SQL, Spark, Airflow, Kafka, Flink, Iceberg, Trino, Pinot, AWS
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