What Expert-Level Productivity Actually Looks Like Now

Webinar Description

Scott Poulin has been deep in the Databricks platform for years — building pipelines, tuning orchestration, solving the kinds of data engineering problems that don't fit neatly into vendor demos. This session is a behind-the-scenes look at how his daily work has changed as AI and automation capabilities on the platform have matured.

This isn't a product pitch. It's a practitioner pulling back the curtain on what expert-level data engineering productivity looks like right now. Scott will walk through real workflows — the ones he actually uses — showing where AI-assisted development, declarative pipeline design, and automated governance have compressed timelines he used to measure in weeks down to hours. He'll also be honest about where the tooling falls short and where experienced judgment still carries the load.

The goal is simple: give a room of serious practitioners a clear-eyed view of what's possible today, what's hype, and what changes you should be making to your own workflows based on what's actually working in production.

This is an invite-only session. We're keeping it small to prioritize depth over reach. Expect a working conversation, not a broadcast.

What This Webinar Will Cover

• Scott will cover his actual daily workflow on Databricks — what's automated, what's AI-assisted, what's still manual

• Delta Live Tables in practice: the real productivity gains and the sharp edges

• Using Databricks Assistant and LLM-powered tooling for pipeline authoring, debugging, and documentation — where it saves real time vs. where it creates false confidence

• Automated data quality patterns that hold up under production pressure

• Unity Catalog as operational infrastructure, not just a governance checkbox

• The workflow orchestration patterns he's settled on after testing a dozen approaches