Senior Analytics EngineerRobinhood • San Francisco, California, United States
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Senior Analytics Engineer
Robinhood
- San Francisco, California, United States
- San Francisco, California, United States
À propos
5+ 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 mentality
Ability to work in a fast-paced, and highly multi-functional environment
What the job involves
As a Senior Analytics Engineer, you will be a key architect of Robinhood’s data foundation. You’ll be responsible for the design and development of high-performance ETL pipelines, data models, and analytics tools that fuel critical decisions across the company
Your work will directly influence product strategy, regulatory reporting, and operational efficiency, ensuring Robinhood remains agile and data-driven at scale
This is more than a build role—you’ll help define metrics, shape datasets, and set the standards for analytics excellence across the company. The systems and frameworks you create will have a long-lasting impact on Robinhood’s growth trajectory
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 critically important business, product, and regulatory needs
Build internal frameworks and tooling to make high-quality data more accessible and actionable across the organization
Collaborate with data scientists to transform raw data into meaningful insights that directly shape business and product outcomes
Champion analytics best practices and drive a culture of data literacy, empowering teams to expertly explore and interpret data on their own
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Compétences linguistiques
- English
Avis aux utilisateurs
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