Software Developer, Data Engineering

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, keep reading.

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are focused on delivering meaningful results. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

With a strong and growing engineering hub in Toronto, our teams in Canada play a critical role in building financial products that serve millions of customers! The Data Engineering team creates and maintains the foundational datasets that power analytics, experimentation, and machine learning across Robinhood. This includes application events, database snapshots, and derived metrics that help teams understand product performance.

As a Software Developer, you will design and build scalable data pipelines and tooling that support decision-making across the company. You will partner with engineers, data scientists, and business teams to develop intuitive data models and improve how data is generated and consumed. This role provides an opportunity to shape how data systems evolve as product and business needs grow!

This role is based in our Toronto, ON office, with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

• →Build and maintain key datasets across Robinhood product areas, evolving them as use cases expand
• →Develop scalable data pipelines using Python, Spark, and Airflow to ingest and process data into the data lake
• →Work with upstream engineering teams to improve how data is generated and structured
• →Partner with data users to understand usage patterns and design clear, usable data models
• →Contribute to shared data engineering tooling and establish consistent development standards

• You have 3+ years of experience building end-to-end data pipelines
• You have hands-on software engineering experience and can write production-level Python code for applications or services
• You have experience building and maintaining large-scale data pipelines using frameworks such as Spark or Flink
• You are proficient in SQL, including tools such as Presto or Spark SQL
• You can work across the data stack, including data infrastructure and analytics platforms, and collaborate effectively with partners