As I was scrolling through job listings, I stumbled upon an Analytics Engineer role at Robinhood. What caught my attention was the tech stack required for the position. There was no mention of a data warehouse, but instead, a focus on SQL, Python, PySpark, and ETL pipelines.
The job description highlighted the need for strong expertise in advanced SQL, Python scripting, and Apache Spark (PySpark, Spark SQL) for data processing and transformation, as well as proficiency in building, maintaining, and optimizing ETL pipelines using modern tools like Airflow or similar.
This got me wondering: what’s behind Robinhood’s tech stack? Are they using a cloud-based data warehouse, or perhaps a custom-built solution?
As someone interested in data engineering, I’m curious to know how Robinhood handles its data pipeline. Do they have a centralized data warehouse, or is it more distributed? How do they process and transform their data for analytics and reporting?
If you’re working at Robinhood or have insight into their tech stack, I’d love to hear about it. Share your knowledge!
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*Further reading: Airflow Documentation*