Data Engineering Podcast


This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.

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19 February 2018

Data Teams with Will McGinnis - Episode 19 - E19

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Summary

The responsibilities of a data scientist and a data engineer often overlap and occasionally come to cross purposes. Despite these challenges it is possible for the two roles to work together effectively and produce valuable business outcomes. In this episode Will McGinnis discusses the opinions that he has gained from experience on how data teams can play to their strengths to the benefit of all.

Preamble

  • Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure
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  • A few announcements:
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    • If you work with data or want to learn more about how the projects you have heard about on the show get used in the real world then join me at the Open Data Science Conference in Boston from May 1st through the 4th. It has become one of the largest events for data scientists, data engineers, and data driven businesses to get together and learn how to be more effective. To save 60% off your tickets go to dataengineeringpodcast.com/odsc-east-2018 and register.


  • Your host is Tobias Macey and today I’m interviewing Will McGinnis about the relationship and boundaries between data engineers and data scientists

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • The terms “Data Scientist” and “Data Engineer” are fluid and seem to have a different meaning for everyone who uses them. Can you share how you define those terms?
  • What parallels do you see between the relationships of data engineers and data scientists and those of developers and systems administrators?
  • Is there a particular size of organization or problem that serves as a tipping point for when you start to separate the two roles into the responsibilities of more than one person or team?
  • What are the benefits of splitting the responsibilities of data engineering and data science?
    • What are the disadvantages?


  • What are some strategies to ensure successful interaction between data engineers and data scientists?

  • How do you view these roles evolving as they become more prevalent across companies and industries?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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