Analytics Developer

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
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.Responsibilities
Work with product, engineering, and data science teams to define metrics and deliver analytics solutions, from data ingestion to reportingDesign and maintain scalable ETL pipelines and data models using tools such as Airflow and SparkBuild analytics products that support business, product, and regulatory reporting needsDevelop internal tools and frameworks to improve data accessibility and usability across teamsPartner with data scientists to turn raw data into insights that inform product and business decisionsPromote consistent analytics practices and support teams in using data effectivelyRequirements
3+ years of experience in analytics engineering, data engineering, data science, or a related fieldStrong experience with SQL, Python, and Apache Spark for data processingExperience building and maintaining ETL pipelines using tools such as Airflow or similarExperience creating dashboards using tools such as Superset, Looker, or TableauFamiliarity with version control systems like Git and modern development workflowsAbility to work effectively with partners across engineering, product, and data teamsWhat We Offer
Challenging, high-impact work to grow your careerPerformance driven compensation with multipliers for outsized impact, bonus programs, and equity ownershipTop tier benefits to fuel your work, including supplemental health insurance, ancillary insurance, and mental health support programsLifestyle wallet - a highly flexible employer-paid benefits spending account for expenses beyond traditional benefits such as wellness, childcare, learning, and moreTime off to recharge including company holidays, paid time off, sick time, paid volunteer time off, parental leave, and moreExceptional office experience with catered meals, events, and comfortable workspacesMonthly commuter stipend to help offset in-office commuting costsCompensation
Base Pay Range (Toronto, ON):
$145,000 - $170,000 CADIn addition to base pay, this role is 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.
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