Senior Software Engineer, Data Engineering

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. The Data Engineering team builds and maintains the foundational datasets that power decision-making across Robinhood. We design reliable, scalable data systems that support product analytics, growth strategy, financial reporting, experimentation, and machine learning. The team partners closely with Product, Engineering, Data Science, and Finance to ensure accurate, well-modeled data is available to teams across the company. Our work directly influences how Robinhood measures performance, improves customer experience, and scales its products. As a Senior Data Engineer, you will design, build, and evolve core datasets that track product performance and company-wide metrics. You will develop scalable data pipelines that ingest application events and database snapshots into our data lake, ensuring high data quality and reliability. You’ll collaborate with application engineers to improve data generation patterns and with analytics teams to design intuitive, well-documented data models. This is an opportunity to shape the technical foundation that supports data-informed decisions across the organization! This role is based in our Menlo Park, CA 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 - 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 - 5+ 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. What we offer - Challenging, high-impact work to grow your career - Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching - Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents - Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more - Employer-paid life & disability insurance, fertility benefits, and mental health benefits - Time off to recharge including company holidays, paid time off, sick time, parental leave, and more! - Exceptional office experience with catered meals, events, and comfortable workspaces. In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + 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. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process. Base Pay Range: Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC) $196,000—$230,000 USD Zone 2 (Denver, CO; Westlake, TX; Chicago, IL) $172,0

5+ 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. 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.

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.