Analytics Engineer

3+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field.

Strong expertise in advanced SQL, Python scripting, and Apache Spark (PySpark, Spark SQL) for data processing and transformation.

Proficiency in building, maintaining, and optimizing ETL pipelines, using modern tools like Airflow or similar.

Experience in building polished and performant dashboards using tools like Superset, Looker, Tableau.

Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.

A strong product approach.

Partner cross-functionally

with product, engineering, and data science teams to scope and deliver high-impact analytics initiatives, from metric definitions to fully automated reporting solutions.

Design and maintain reliable, scalable ETL pipelines and data models

using modern data tools (e.g., Airflow, Spark), ensuring performance and accuracy at scale.

Lead end-to-end development

of analytics products—from ingestion to visualization—that meet mission-critical business, product, and regulatory needs.

Robinhood’s

Analytics Engineering

team, part of the Data Science organization, is the backbone of our decision-making ecosystem. We design and deliver

foundational data products

that power everything from product innovation to regulatory compliance and operational excellence. Our mission is simple but ambitious:

enable every team at Robinhood to access trustworthy, scalable, and self-serve analytics