The Data Cloud — Cloud Data Platform for AI & Analytics
The consensus on Snowflake: Choose Snowflake for massive-scale engineering challenges and top-tier compensation — but be ready for a culture in transition and variable work-life balance.
Founded in 2012 by Benoit Dageville, Thierry Cruanes, and Marcin Zukowski, Snowflake pioneered the cloud data warehouse by separating storage from compute. Now building the Data Cloud — encompassing data warehousing, data lakes, data sharing, data engineering, and AI/ML across AWS, Azure, and GCP. The engineering culture is technically demanding, centered on large-scale distributed systems. Culture is in transition under CEO Sridhar Ramaswamy (appointed 2024) — there's a strong technical foundation, but employee sentiment is mixed on recent leadership changes and organizational restructuring.
Snowflake runs natively on AWS, Azure, and GCP with a single codebase. Engineers work on cross-cloud infrastructure at massive scale — processing exabytes of data across distributed clusters worldwide.
Building Snowpark for AI/ML workloads — enabling data scientists to run Python, Java, and Scala directly in Snowflake's compute layer. Cortex AI brings LLMs to the Data Cloud. Explore the Data Cloud →
Large engineering organization with specialized teams across query optimization, storage, compute, security, and AI/ML. Teams are organized around product areas with dedicated engineering leads and cross-functional collaboration.
Explore open roles at Snowflake below.