What is your experience with Snowflake? Have you loaded data into it?

I have worked with Snowflake for two years, designing data warehouses and loading data from various sources. Snowflake’s architecture separates storage, compute, and services, allowing independent scaling. For loading, I use Snowflake stages: internal stages for data stored in S3/ADLS, external stages for public data, and user‑defined stages for local files. The COPY INTO command is my primary tool; I configure file formats (CSV, JSON, Parquet), set header and compression options, and use the ON_ERROR clause for fault tolerance. I also automate incremental loads with Snowpipe, which watches a stage for new files and triggers ingestion. For large datasets, I partition by date and use clustering keys to improve query performance. I monitor load performance via Snowflake’s Query History and adjust warehouse size or use multi‑cluster warehouses for concurrency.