Staff Software Engineer, Product Risk

Stripe · Toronto · 8122 Data Foundations · listed August 6, 2026

The shape of it

Seniority
Staff
Experience asked
10+ years
Where
Not stated
Requirements listed
8
Length
735 words

In the posting’s own words

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.

What it asks for · 8

  • 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 autonomy and responsibility in an ambiguous environment
  • Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment

Also a plus

  • 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
  • Influencing open-source contributions
  • Experience creating and maintaining data marts / warehouses to power business reporting needs
  • Experience collaborating with Product, Go-To-Market, or 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

What the job covers

  • 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

Tools and skills named

Data
  • Data pipelines4×
  • Airflow2×
  • Spark2×
Cloud & infra
  • Kafka2×
  • AWS
Languages
  • Java
  • Scala
  • SQL
Models & research
  • LLM
  • Machine learning
Ways of working
  • Cross-functional
  • Mentorship
Go to market
  • Go-to-market
Operations & finance
  • Recruiting

Words the posting leans on

  • data29×
  • product7×
  • experience6×
  • data pipelines4×
  • requirements4×
  • warehouses4×
  • building3×
  • business3×
  • data engineering3×
  • deliver3×
  • scale3×
  • ambiguous2×
  • capabilities2×
  • cases2×
  • collaborate2×
  • customer2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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How this page was made

An automated read of a public job posting, fetched August 25, 2026 and last changed by Stripe on August 18, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.