Robinhood is seeking a Senior Data Engineer to design, build, and evolve core datasets and scalable data pipelines that track product performance and company-wide metrics. You will ingest application events and database snapshots into our data lake, ensure high data quality, and collaborate with application engineers to improve data generation patterns and with analytics teams to design intuitive, well-documented data models. This role is based in Menlo Park, CA, with in-person attendance expected at least 3 days per week. What you’ll do: 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 d

Robinhood is seeking a Senior Data Engineer to design, build, and evolve core datasets and scalable data pipelines that track product performance and company-wide metrics. You will ingest application events and database snapshots into our data lake, ensure high data quality, and collaborate with application engineers to improve data generation patterns and with analytics teams to design intuitive, well-documented data models. This role is based in Menlo Park, CA, with in-person attendance expected at least 3 days per week. What you’ll do: 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 d