Senior Software Engineer, Data Engineering
AI summary of the role
Senior Data Engineer on the Data Engineering team at Robinhood, responsible for designing and building core datasets and scalable data pipelines that power product analytics, financial reporting, and machine learning across the company.
What you’ll do
- Help define and build key datasets across all Robinhood product areas and lead their evolution as use cases grow.
- Build scalable data pipelines using Python, Spark, and Airflow to move data from different applications into the 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.
What you’ll bring
- 5+ years of professional experience building end-to-end data pipelines.
- Hands-on software engineering experience writing 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.
Technologies
Python · Spark · Airflow · Flink · SQL · Presto · Spark SQL · data lake · data pipelines
About Robinhood
Mobile-first retail brokerage for US consumers, expanding into crypto derivatives (Bitstamp), banking, retirement, and RIA custody (TradePMR).
Public
Source and classification
Internal deployment & tooling · Evidence for this classification:
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,
More from the job description
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 desi [... source excerpt omitted ...] es 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
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