#123 Building Fast and Fun Data Projects - with Mehdi Ouazza
In this episode, I sit down with Mehdi Ouazza - data tinkerer, indie hacker, and content creator - who's always up to something interesting in the world of data and AI.We started with DuckDB but quickly veered off into much more exciting territory: side projects, voice-to-SQL with actual quacks, the power of local models, and why WebGPU might be one of the most underrated browser technologies today.We also talked about how we teach and learn data engineering in 2025: the importance of fun, interactivity, and why we both dream of creating a data engineering game that’s part "Among Us" and part serious skills training.Mehdi shares what tools he's using, where he sees GenAI actually helping—not replacing—engineers, and how he's building courses and meetups that inspire creativity in technical work.Perfect for data folks who like to experiment, educators looking for inspiration, or anyone wondering how far a fun idea can go with the right mix of curiosity and tooling.
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#122 Why Writing Is Thinking , and What Data Engineers Can Learn from It - with Simon Späti
In this podcast episode, I’m joined by Simon Späti, long-time BI and data engineering expert turned full-time technical writer and author of the living book Data Engineering Design Patterns. We talk about:His 20-year journey from SQL-heavy BI to modern Data EngineeringWhy switching from employee to full-time author wasn’t planned, but necessaryHow he uses a “Second Brain” system to manage and publish his knowledgeWhy writing is a tool for learning, not just sharingThe concept of convergent evolution in data tooling: when old and new solve the same problemThe underrated power of data modeling and pattern recognition in a hype-driven industry Simon also shares practical advice for building your own public knowledge base, and why Markdown and simplicity still win in the long run.Whether you're into tools, systems, or lifelong learning, this one’s a thoughtful deep dive.***About Simon Späti:Simon is a Data Engineer and Technical Author with 20+ years of experience in the data field. He's the author of the Data Engineering Blog (ssp.sh), curator of the Data Engineering Vault (vault.ssp.sh), and currently writes a book about Data Engineering Design Patterns (dedp.online). Simon maintains an awareness of open-source data engineering technologies and enjoys sharing his knowledge with the community.Socials: Bluesky, LinkedIn, Twitter/X, YouTube
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#121 From Application Dev to AWS Hero: A Journey in Tech & Impact - with Johannes Koch
In this episode, I’m joined by Johannes Koch, Principal Engineer and AWS DevTools Hero, to talk about the real DevOps mindset, the evolution of developer experience, and how community work changed his career.Johannes shares how starting in QA and support gave him a unique edge in understanding users, why building a proper CI/CD pipeline should come before writing code, and how the AWS Community Builders program helped him grow into his current role.We also dive into:What DevOps culture actually means beyond automationHis take on GitOps and why CI/CD is still underratedBehind the scenes of the AWS Heroes ProgramCreating content, mentoring others, and avoiding the trap of tech hypeWhether you're starting out in DevOps or deep into cloud architecture, Johannes' insights are packed with value for data and AI professionals.Links:Johannes on LinkedInYouTube: @cicdonawsAWS Community Day DACH
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#120 Teaching Data Engineering Like It’s Done on the Job - with Deepak Goyal
In this episode, I sit down with Deepak Goyal, the founder of AzureLib, to talk all things data engineering, cloud platforms, and how to teach the next generation of engineers.We explore why Azure became his go-to, how real-world projects beat theory every time, and why tools like ChatGPT are great assistants, but no substitute for structured learning and solid fundamentals.Follow Deepak on LinkedIn: https://www.linkedin.com/in/deepak-goyal-93805a17/Check out AzureLib: azurelib.comLearn Data Engineering with me: learndataengineering.com
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#119 Recruiting is harder than I thought
In this episode of the Plumbers of Data Science podcast, I dive into the challenges of recruiting today, from overwhelming job application volumes to reaching out directly to recruiters.I’m testing new strategies to make the process smoother for everyone involved, focusing on fresh job listings and fostering connections with hiring managers who need skilled engineers. My goal? To secure five job placements in Germany by year’s end!Have thoughts on today’s job market, or tried the Easy Apply feature yourself? Drop a comment below—I’d love to hear your experience!
Data Engineering is the plumbing of data science. Almost invisible, but super important and a big mess when done wrong.
We talk about interesting Data Engineering trends and topics. I also train Data Engineering in my Data Engineering Academy at LearnDataEngineering.com
New Zealand