Anton Grinevsky

Building resilient data transformation pipelines requires more than just writing code — it demands a structured lifecycle that ensures reliability, performance and maintainability. This session explores best practices for managing the data pipeline development lifecycle in Snowflake, from creation in a rich IDE to robust testing, monitoring and debugging. We’ll cover strategies for version control, data quality testing, leveraging telemetry for proactive monitoring, and using UI-driven tools for faster debugging. Attendees will gain actionable insights into streamlining development workflows, reducing downtime and ensuring data integrity across the pipeline.