Staff Software Engineer, Product Risk

United States Digital Space LLC; Toronto; On-site; CAD 140,000 - 180,000; Full time

Job summary

United States Digital Space LLC is seeking a Staff Data Engineer in Toronto to lead the data engineering team, build scalable data pipelines, and own end-to-end data infrastructure for payments, risk, and product analytics.

You will collaborate across product and engineering teams, drive data quality, and leverage modern technologies like Iceberg, Kafka, Flink, Spark, Airflow, and AWS to enable trusted data platforms for the company.

Qualifications

• 10+ years of experience building and operating data systems, pipelines, warehouses, and leading teams.
• Strong background in data engineering with distributed data frameworks.
• Ability to debug data quality issues and dive into data inconsistencies.
• Backend development experience (Scala/Java/Go) and strong SQL.
• Excellent collaboration with product and engineering teams.

Responsibilities

• Lead the technical outcomes for a team of engineers, providing mentorship and guidance.
• Partner with recruiting to attract and hire top talent.
• Deliver data pipelines that scale with reliability and efficiency.
• Develop expertise and manage SLAs for data pipelines and web applications.
• Collaborate with product managers to create canonical datasets and data warehouses.
• Leverage AI/LLM and Agents to analyze data on ambiguous problems.
• Drive key data initiatives from planning to delivery with high quality.

Skills

Backend language (Scala/Java/Go)

SQL

Data pipelines

Leadership

Autonomy

Tools

Iceberg

Kafka

Change Data Capture

Flink

Spark

Airflow

Hive Metastore

Pinot

Trino

AWS Cloud

Job description

Who we are

About the company

the company is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use the company 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 the company\'s single source of truth data engineering layer for Payments, Risk, and Product — we enable the company 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 the company, 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 the company 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 the company 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 the company, 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 the company 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