Spark ⚡ vs dbt: Choosing Your Engine for Modern Data Workflows

Struggling to decide when to fire up a Spark cluster and when to lean on dbt’s elegant SQL models? You’re not alone! Join the Infolob Data & AI crew for a relaxed, online evening of candid stories, live demos, and open Q&A where we will:

• Demystify both tools—what they’re great at, where they stumble, and how they can play nicely together.
• Walk through three real-world architecture patterns (Spark-first, dbt-first, and hybrid) you can copy-paste into your own projects.
• Run a mini-pipeline demo: Spark cleans messy click-stream data → dbt builds a revenue mart → lineage & tests light up—no slides-only talk here!

The meetup is in collaboration with Infolob Global Inc.
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Who should attend?
Data engineers, analytics engineers, BI developers, architects, and anyone curious about the modern ELT / lakehouse ecosystem. Whether you’re a hardened PySpark coder or just dipping your toes into dbt, you’ll leave with practical “when to use what” guidelines.
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Agenda (IST)

4:00 PM to 4:10 PM: Virtual lobby opens — say hi in chat, try the ice-breaker poll
4:10 PM to 4:15 PM: Welcome & quick update on the meetup group and Infolob Data + AI CoE as well as DBT Practice.
4:15 PM to 5:40 PM: Talk + live demo (DBT Core and Redshift) - Speaker: Durga Gadiraju
5:40 PM to 6:00 PM: Interactive Q&A, lightning polls & Wrap-up

Wait for our email after the session for resources, and after-chat followup (optional)

Can’t make the whole session? RSVP anyway and we’ll send the recording and slide deck to everyone who registers. But don't miss this live session.
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How to Join?
A Zoom link (and calendar invite) will be provided and emailed to all RSVPs. Make sure your Meetup notifications are enabled, or check the “Messages” tab on the event page.

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Perks

• Live-code repo & slide deck drop in chat and also via email right after the session
• Raffle for cloud-credit gift cards and Infolob swag—must be present at drawing to win!

👋 RSVP now, grab your favorite beverage, and get ready to settle the Spark-vs-dbt debate—spoiler: the answer might be “both!”