Software Developer, Data Engineering

About Us

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you're ready to be at the epicenter of this historic cultural and financial shift, we want to hear from you.

About the Role

With a strong and growing engineering hub in Toronto, our teams in Canada are essential to building exceptional financial products and supporting our mission to democratize finance for all.

Robinhood is a metrics-driven company where data is foundational to every decision—from long-term strategy to daily operations. As a Software Developer on our Data Engineering team, you'll help build and maintain the core datasets that power analytics, experimentation, and machine learning across Robinhood. These foundational data assets include application events, database snapshots, and derived metrics that track the performance of our products.

You'll work closely with engineers, data scientists, and business teams to design scalable, intuitive pipelines and tooling. This is a unique opportunity to influence how data supports our decision-making for years to come.

Responsibilities

• Help define and build key datasets across all Robinhood product areas. Lead the evolution of these datasets as use cases grow.
• Build scalable data pipelines using Python, Spark and Airflow to move data from different applications into our data lake.
• Partner with upstream engineering teams to enhance data generation patterns.
• Partner with data consumers across Robinhood to understand consumption patterns and design intuitive data models.
• Ideate and contribute to shared data engineering tooling and standards.
• Define and promote data engineering best practices across the company.

Requirements

• 3+ years of professional experience building end-to-end data pipelines
• Hands-on software engineering experience, with the ability to write production-level code in Python for user-facing applications, services, or systems (not just data scripting or automation).
• Expert at building and maintaining large-scale data pipelines using open source frameworks (Spark, Flink, etc)
• Strong SQL (Presto, Spark SQL, etc) skills.
• Experience solving problems across the data stack (Data Infrastructure, Analytics and Visualization platforms)
• Expert collaborator with the ability to democratize data through actionable insights and solutions.

Compensation

Base Pay Range: $136,000 – $160,000 CAD (Toronto, ON)

In addition to the base pay range listed above, this role is also eligible for bonus opportunities, equity, and benefits.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands.