About the team + 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 and data is foundational to all key decisions from growth strategy to product optimization to our day-to-day operations. We are looking for a Software Engineer, Data Engineering to build and maintain foundational datasets that will allow us to reliably and efficiently power decision making at Robinhood. These datasets include application events, database snapshots, and the derived datasets that describe and track Robinhood's key metrics across all products. You’ll partner closely with engineers, data scientists and business teams to power analytics, experimentation, and machine learning use cases. We are a fast-paced team in a fast growing company and this is a unique opportunity to help lay the foundation for reliable, impactful, data-driven decisions across the company for years to come.

The role is located in the office location(s) listed on this job description which will align with our in-office working environment. Please connect with your recruiter for more information regarding our in-office philosophy and expectations.

What you’ll do 

• 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.

What you bring

• 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.

Bonus points:

• Passion for working and learning in a fast-growing company.

Our team is committed to providing an inclusive and welcoming interview experience for all candidates. If you require a specific accommodation during the application or interview process due to a physical or mental condition, please complete this Applicant Accommodation Form to notify our team. The form should only be completed if you need a specific accommodation.