Modern data engineering leverages Python to build robust, scalable, end-to-end workflows. In this talk, we will cover how Snowflake offers you a flexible development environment for developing Python data pipelines, performing transformation at scale, orchestrating and deploying your pipelines at scale. Topics we’ll cover include: – Ingest: Data source APIs, Snowflake file-to-read and ingest data of any format when files arrive, with sources outside Snowflake – Develop: Packaging (artifact repo), Python runtimes, IDE (Notebook, vscode) – Transform: Snowpark pandas, UDFs, UDAFs – Deploy: Tasks, Notebook scheduling

Apache Iceberg provides an open storage standard that can democratize your data stored in disparate data lakes by providing freedom and interoperability to use various data processing engines. Join this session to explore Snowflake’s latest advancements for data engineering on Snowflake Iceberg Tables. We’ll dive into newly launched features that enhance interoperability as well as bring Snowflake’s ease of use to your Iceberg data lakes.

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