PySpark in Foundry Walkthrough

f you already know some PySpark or want to understand how it is used inside Foundry, this session will help you connect the dots. We’ll focus on how data engineering logic is applied in a Foundry context rather than discussing PySpark in isolation.

This is especially useful for professionals who understand data engineering in general but want a more implementation-oriented understanding of how Foundry workflows are built and maintained.

What we can cover:

• PySpark-based transformation thinking in Foundry.
• Common implementation patterns and debugging approach.
• Structuring logic for maintainability and readability.
• Translating business requirements into data workflows.
• Questions from your own learning or project use case.

Best for:

• Data engineers and analytics engineers.
• Professionals moving into Foundry development work.
• Learners who want practical rather than purely academic guidance.

What you’ll leave with:

• Better clarity on how PySpark is applied in Foundry contexts.
• Practical implementation guidance.
• A clearer idea of what to learn next based on your current level.