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Snowflake Python Data Engineer

Mastering Python Integration with Snowflake: Building High-Performance Data Pipelines, Automation, and Observability

Duration

3 Days (8 hours per day)

Level

Intermediate to Advanced Level

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This three-day course equips you with the expertise to integrate Python within the Snowflake AI Data Cloud. You will design and deploy high-performance data engineering solutions utilizing the Snowflake Python API and Snowpark. The course combines lectures, demos, interactive labs, and in-depth discussions to ensure a comprehensive learning experience.

ACQUIRED SKILLS:

  • Explain the distinctive features of Snowflake’s platform and its integration with Python.
  • Configure and establish secure connections to Snowflake using the Snowpark Session object.
  • Design, code, and deploy custom Python functions within Snowflake as User Defined Functions (UDFs).
  • Create and encapsulate reusable logic using Stored Procedures.
  • Organize and manage automated workflows with Snowflake tasks and Directed Acyclic Graphs (DAGs).
  • Automate recurring data tasks using Snowflake’s task scheduling capabilities.
  • Monitor and debug data processes while implementing observability techniques in Snowflake and Python
  • environments.
  • Leverage Anaconda integration in Snowflake to enhance data solutions with specialized Python libraries
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  • Data Engineers
  • Data Scientists
  • Data Application Developers
  • Database Architects
  • Database Administrators
  • Data Analysts with programming experience
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  • Using Snowsight
  • Snowflake Structure
  • Python API Concepts
  • Core Classes and Operations
  • Cloning
  • Time Travel
  • Metadata
  • Query Result Cache
  • Data Cache
  • Snowpark
  • Snowflake Connector for Python
  • Drivers, Clients, and Connectors Overview
  • Snowflake Notebook API
  • Data Loading Objects
  • Transformations and Copy Options
  • Bulk vs. Continuous Data Loading Approaches
  • Semi-structured Data
  • Snowpipe
  • Snowflake Data Loading Best Practices
  • Loading Semi-structured Data
  • Dynamic Tables
  • Creating and Managing Streams
  • UDFs and Stored Procedures
  • External Network Access
  • Transformations with Unstructured Data
  • Creating Tasks
  • Creating a DAG
  • Streamlit
  • Data Sharing
  • Observability on Snowflake
  • Outbound Notifications
  • Snowflake Alerts
  • Data Pipeline Logging
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  • Basic Python coding proficiency.
  • Familiarity with basic SQL.

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