Table of Contents

  1. Data transformation
  2. Data testing
  3. Implementations + deployment
  4. Documentation + metadata
  5. The modern data stack
  6. Data dream teams

How to start your analytics engineering team

Andres is the Analytics Engineering Lead at goPuff, helping to scale the digital convenience store's mission to deliver the moment for millions of customers. He previously led the analytics team at La Colombe Coffee Roasters, the fastest growing Ready-to-Drink Coffee company in the world. When he's not data wrangling, you can typically find him trail running outside Philadelphia or preparing an elaborate dinner for two.

Originally presented on 2020-12-12

At many organizations, dbt and the competency of Analytics Engineering are introduced well after the establishment of an analytics team. It's easy to agree in principal with all the benefits and value added by this new tool and analytics practice, but getting there can be a challenge. As with most tool implementations or team restructuring, there is often a long, painful transition from whatever was being done previously to the new future.

In this presentation we'll learn from Andres' experience implementing analytics engineering practices in both a greenfield situation (La Colombe) and his current successes (and failures!) of implementing analytics engineering at an already established organization (goPuff).

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