Building a strong personal brand is your ticket to standing out from your competition in today's difficult job market. During this episode, you'll learn why and how you should build a personal brand to elevate your career. You'll hear from some of the biggest names in data: Kate Strachnyi, Founder of DATAcated, and Andreas Kretz, Founder of Learn Data Engineering. Kate and Andreas will share their best strategies, tips, and actionable advice to put you on a path to building a successful brand that will accelerate your career.   What You'll Learn: Why a personal brand is critical for success in 2025 and beyond What a strong personal brand should look like How you can start making progress on your personal brand today   This session was part of our OPEN CAMPUS week in October, which included 6 days of live expert sessions.   Register for free to be part of the next live session: https://bit.ly/3XB3A8b    

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In this episode, I talk with Andreas Kretz (https://www.linkedin.com/in/andreas-kretz/) who is an amazing resource for the data engineering community. He runs an incredibly affordable data engineering bootcamp called Learn Data Engineering (https://learndataengineering.com) and also has an extensive YouTube (https://www.youtube.com/channel/UCY8mzqqGwl5_bTpBY9qLMAA). 

We talked about how Andreas got started with data engineering, why he like it so much, and how others can get started. I also share my story of interviewing with Facebook for a data engineering position. 

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Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

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If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

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We talked about:

Andreas’s background Why data engineering is becoming more popular Who to hire first – a data engineer or a data scientist? How can I, as a data scientist, learn to build pipelines? Don’t use too many tools What is a data pipeline and why do we need it? What is ingestion? Can just one person build a data pipeline? Approaches to building data pipelines for data scientists Processing frameworks Common setup for data pipelines — car price prediction Productionizing the model with the help of a data pipeline Scheduling Orchestration Start simple Learning DevOps to implement data pipelines How to choose the right tool Are Hadoop, Docker, Cloud necessary for a first job/internship? Is Hadoop still relevant or necessary? Data engineering academy How to pick up Cloud skills Avoid huge datasets when learning Convincing your employer to do data science How to find Andreas

Links:

LinkedIn: https://www.linkedin.com/in/andreas-kretz Data engieering cookbook: https://cookbook.learndataengineering.com/ Course: https://learndataengineering.com/

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