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 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.

Robinhood’s Analytics Engineering team, part of the Data Science organization, builds the data foundation that supports decision-making across the company. The team develops data products that support product development, regulatory requirements, and business operations. You will work closely with product managers, engineers, and data scientists to transform raw data into reliable, usable datasets.

As an Analytics Engineer, you will design and build ETL pipelines, data models, and analytics tools that support key business decisions. You will contribute to defining metrics, improving dataset quality, and establishing standards for analytics development. This role offers the opportunity to influence how teams access and use data across Robinhood while supporting systems that operate at scale!

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.

What you’ll do

• Work with product, engineering, and data science teams to define metrics and deliver analytics solutions, from data ingestion to reporting
• Design and maintain scalable ETL pipelines and data models using tools such as Airflow and Spark
• Build analytics products that support business, product, and regulatory reporting needs
• Develop internal tools and frameworks to improve data accessibility and usability across teams
• Partner with data scientists to turn raw data into insights that inform product and business decisions
• Promote consistent analytics practices and support teams in using data effectively

What you bring 

• You have 3+ years of experience in analytics engineering, data engineering, data science, or a related field
• You have strong experience with SQL, Python, and Apache Spark for data processing
• You have experience building and maintaining ETL pipelines using tools such as Airflow or similar
• You have experience creating dashboards using tools such as Superset, Looker, or Tableau
• You are familiar with version control systems like Git and modern development workflows
• You can work effectively with partners across engineering, product, and data teams

What we offer

• Challenging, high-impact work to grow your career
• Performance driven compensation with multipliers for outsized impact, bonus programs, and equity ownership
• Top tier benefits to fuel your work, including supplemental health insurance, ancillary insurance, and mental health support programs
• Lifestyle wallet - a highly flexible employer-paid benefits spending account expenses beyond traditional benefits such as wellness, childcare, learning, and more.
• Time off to recharge including company holidays, paid time off, sick time, paid volunteer time off, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.
• Monthly commuter stipend to help offset in-office commuting costs

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.

AI Usage Disclosure: Robinhood uses artificial intelligence (AI) tools to support parts of our recruiting process. These tools enhance the efficiency and consistency of our hiring process; however, all hiring decisions are made by our hiring teams.

Vacancy Notice: This job posting represents an existing vacancy that we are actively seeking to fill.