Snowflake and BigQuery are cloud data warehouses: managed services that store very large volumes of data and let you query them in SQL, with storage and compute kept separate and billed by usage.
Snowflake is an independent vendor whose platform runs on AWS, Azure and Google Cloud. It isolates workloads in virtual warehouses that are started, stopped and sized on demand. BigQuery is Google Cloud's service: fully serverless, it is billed either by the amount of data read per query or by reserved capacity.
Both serve as the foundation of the modern data stack: ingestion tools load data into them, dbt transforms it, a BI tool presents it. They compete directly with lakehouse architectures such as Databricks.
Why it matters when hiring
These tools are the daily work of Data Engineers and Analytics Engineers. Writing SQL on them is easy; running them properly is harder. Ask how the candidate kept the bill under control (partitioning, clustering, expensive queries found and fixed) and how they organize access rights. A profile that has never looked at what a query costs has not yet worked at scale.