Building And Managing Data Teams And Data Platforms In Large Organizations With Ashish Mrig
Data Engineering Podcast
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Evolving Data Engineering: Balancing Analytics and Machine Learning Workloads
This chapter explores the transformation of data engineering from supporting analytical queries to handling extensive machine learning workloads. It highlights the significance of design in catering to varied stakeholder needs and presents techniques for improving data processing efficiency and scalability.
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Summary
Data engineering is a relatively young and rapidly expanding field, with practitioners having a wide array of experiences as they navigate their careers. Ashish Mrig currently leads the data analytics platform for Wayfair, as well as running a local data engineering meetup. In this episode he shares his career journey, the challenges related to management of data professionals, and the platform design that he and his team have built to power analytics at a large company. He also provides some excellent insights into the factors that play into the build vs. buy decision at different organizational sizes.
Announcements
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
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- Your host is Tobias Macey and today I’m interviewing Ashish Mrig about his path as a data engineer
Interview
- Introduction
- How did you get involved in the area of data management?
- You currently lead a data engineering team at a relatively large company. What are the topics that account for the majority of your time and energy?
- What are some of the most valuable lessons that you’ve learned about managing and motivating teams of data professionals?
- What has been your most consistent challenge across the different generations of the data ecosystem?
- How is your current data platform architected?
- Given the current state of the technology and services landscape, how would you approach the design and implementation of a greenfield rebuild of your platform?
- What are some of the pitfalls that you have seen data teams encounter most frequently?
- You are running a data engineering meetup for your local community in the Boston area. What have been some of the recurring themes that are discussed in those events?
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Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
Closing Announcements
- Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used.
- Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
- If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com) with your story.
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The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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