Taming Data Pipelines: Scaling Databricks & Linting dbt
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Taming Data Pipelines: Scaling Databricks & Linting dbt

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Date

Thu, Jun 4

Time

04:00 PM - 07:30 PM

Price

Free

Website

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About the event

⚠️ Important Note:
PyData Amsterdam is transitioning to Luma.

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Mark your calendars for our upcoming PyData Amsterdam meetup on Thursday, June 4, 2026! We are heading over to Company.info for an evening dedicated to the gritty reality of scaling data infrastructure and applying rigorous engineering to MLOps.

As data platforms grow, so do the bottlenecks. This edition is all about tackling those growing pains head-on. We are going to look under the hood of high-performing data teams to see how they keep their pipelines fast, reliable, and organized at scale. Expect real-world case studies on slashing integration test times during a complex Databricks migration, alongside a deep dive into enforcing architectural standards across sprawling dbt projects using custom Python-based linters.

If you build, maintain, or scale data pipelines, whether as a Data Engineer, ML Engineer, or Data Scientist, this session will equip you with actionable strategies to optimize your daily workflows and tame architectural chaos.

Ready to level up your engineering toolkit? Join us for an evening packed with hard-earned technical insights, great food, and excellent networking with the Amsterdam data community!

Agenda:

  • 18:00 - 18:55: Welcome with food and drinks!
  • 18:55 - 19:00: Intro Company.info
  • 19:00 - 19:45: Talk 1: Scaling our Integration Tests Workflows in Databricks - by Douwe Oosterhout
    19:45 - 20:00: Short break 20:00 - 20:45: Talk 2: dbt-bouncer, a linter for dbt projects - by Pádraic Slattery
  • 20:45 - 21:30: Networking + drinks

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NOTE: We cannot guarantee the accuracy of the information we provide about this event. Visit the event's website to verify details such as date, opening hours, prices and location.

Location

Abram Dudok van Heelstraat 2, meetup1, Amsterdam

Abram Dudok van Heelstraat 2, meetup1, AmsterdamOpen in Google Maps

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