Staff Software Engineer, Risk Data Engineering

Stripe; Toronto; On-site; CAD 180,000 - 240,000; Full time

Job summary

Stripe in Toronto seeks a Staff-level data engineer to lead data pipelines and scalable data warehouses, enabling analytics, ML, and trusted data across Stripe.

You will drive data platforms, collaborate with product teams, and mentor engineers to deliver high-quality data solutions with autonomy and impact.

Qualifications

• Staff-level role with 10+ years in data systems and leading teams.
• Strong engineering background with data pipelines in distributed frameworks.
• Experience debugging data quality issues and ensuring data consistency.

Responsibilities

• Lead technical outcomes for a team of engineers and provide mentorship.
• Partner with recruiting to attract top talent and build teams.
• Deliver scalable data pipelines with reliability and efficiency.
• Develop expertise and manage SLAs for data pipelines and apps.

Skills

Data pipelines

Airflow

Spark

Kafka

Flink

SQL

Backend (Scala/Java/Go)

AWS

Change Data Capture

Iceberg/Trino/PINOT

Education

Bachelor's degree in CS/Engineering

Tools

Airflow

Spark

Kafka

Flink

Iceberg

Hive Metastore

Pinot

Trino

AWS Cloud

Job description

Who we are

About Stripe

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.

About the team

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 you’ll do

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.

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 are

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.

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

Preferred qualifications

• 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