Robinhood is looking for a Data Engineer to build and maintain foundational datasets that will allow them to reliably and efficiently power decision making across the company. These datasets include application events, database snapshots, and derived datasets that describe and track Robinhood's key metrics across all products.
Requirements
- 5+ years of professional experience building end-to-end data pipelines
- Proven ability to implement software engineering-caliber code (preferably Python)
- 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)
Responsibilities
- 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.
Other
- The role is located in the office location(s) listed on this job description which will align with our in-office working environment.
- Expert collaborator with the ability to democratize data through actionable insights and solutions.
- Market competitive and pay equity-focused compensation structure
- 100% paid health insurance for employees with 90% coverage for dependents
- Annual lifestyle wallet for personal wellness, learning and development, and more!
