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Engineering Manager, Data

Robinhood Toronto, CanadaEst. Est. CAD 160,000–240,000 / yearSenior

Estimated range based on role, country and industry — not published by the company.

Key requirements

  • Python
  • Spark
  • Aws
  • Machine Learning
  • Data Science
  • Product Management
Join us in building the future of finance. 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. About the team + role 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 wired to make an impact. 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. Our Core Data Engineering team is responsible for designing and building all foundational datasets used across Robinhood and within our operational business areas. We build the foundational data models and core data layers that are consumed by downstream users, ensuring high data quality and reliability. We also develop internal data and AI tooling that enables teams across the company to scale their data development workflows efficiently. Our team collaborates with engineering, product, brokerage, crypto, and marketing teams to expand and grow Robinhood's products around the world ! We also partner with Machine Learning teams to build robust training datasets that power intelligent product features. As the Engineering Manager for our Toronto Data Engineering team, you will lead a team of exceptional engineers and drive the execution of key data initiatives. In this role, you will balance technical leadership with people management, dedicating approximately 60% of your time coaching and 40% to hands-on technical contributions, such as code and architecture reviews. You will drive roadmap planning and establish clear goals for the team, particularly as we expand into new markets and scale systems. Additionally, you will play a crucial role in building more intelligent tooling through AI to help our organization scale! You will collaborate closely with partners in Data Science, Machine Learning, Product Management, and Business Operations to deliver high-quality data products. This role is based in our Toronto, ON office(s), with in-person attendance expected 5 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. What you’ll do Lead, coach, and expand an exceptional team of 10 data engineers based in Toronto, setting a high standard for execution and team growth. Actively participate in technical execution, including code reviews and architecture, assessing data quality, and unblocking daily technical challenges. Define roadmaps and execution plans for core data engineering initiatives, effectively taking on a product management focus to translate ambiguous requirements into clear engineering goals. Build a platform that makes Robinhood's data discoverable, understandable, and usable for both people and AI - through semantic models, metadata, and developer tooling that turn trusted data into a reusable, company-wide asset. Partner with Data Science, ML, and Business Operations teams to build and maintain reliable, scalable data pipelines and foundational datasets that support product expansion and business operations. What you bring 3+ years of experience as an engineering manager, with 5+ years of prior experience as a software engineer or data engineer. Strong hands-on experience with Python and Apache Spark, along with familiarity with cloud platforms like AWS and data technologies such as Databricks, Delta Lake, Flink, or Pinot/Druid. Proven ability to drive clarity in ambiguous situations, take ownership

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