How would you use Snowflake tasks for ELT?

Snowflake tasks enable you to schedule and orchestrate ELT workflows directly within the Snowflake environment. First, you create a SQL script that performs the ELT logic: extract data from external stages or other databases, transform it using Snowflake’s SQL capabilities, and load it into target tables. Then, you define a task that references this script, specifying a schedule (cron expression) or a dependency on another task. Tasks can be chained by setting the "AFTER" clause, allowing you to build complex pipelines where one task triggers the next. Snowflake automatically manages task concurrency and retries, and you can monitor execution via the TASK_HISTORY view. Because tasks run in Snowflake’s compute environment, you avoid moving data out of the warehouse, reducing latency and cost. For more advanced orchestration, you can expose task status via Snowflake’s REST API and integrate with external workflow managers if needed.