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title: Best Data Engineer Things posts — May 2025 | daily.dev
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og:description: The most upvoted Data Engineer Things posts from May 2025, curated by the daily.dev community.
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# Best of Data Engineer Things — May 2025

1. 1  
[](https://daily.dev/posts/airflow-3-and-airflow-ai-sdk-in-action-analyzing-league-of-legends-jlk5tztf9 "Airflow 3 and Airflow AI SDK in Action — Analyzing League of Legends")  
Article  
![Avatar of detlife](https://media.daily.dev/image/upload/s--8lmPEq7G--/f_auto/v1725038518/logos/detlife)Data Engineer Things · 1y  
Airflow 3 and Airflow AI SDK in Action — Analyzing League of Legends  
This post demonstrates how to create an end-to-end data pipeline using Airflow 3 and the Airflow AI SDK to analyze League of Legends data. It covers setting up the environment, exploring the Riot Games API, building a Python client for API interaction, and using AI to generate a champion tier list. The pipeline showcases modern Airflow features like Dynamic Task Mapping and emphasizes newer AI integration capabilities with Large Language Models.  
21  
1
2. 2  
[](https://daily.dev/posts/from-gis-to-data-engineering-mastering-docker-fundamentals-and-best-practices-arnrbop7i "From GIS to Data Engineering: Mastering Docker Fundamentals and Best Practices")  
Article  
![Avatar of detlife](https://media.daily.dev/image/upload/s--8lmPEq7G--/f_auto/v1725038518/logos/detlife)Data Engineer Things · 1y  
From GIS to Data Engineering: Mastering Docker Fundamentals and Best Practices  
The post details a geospatial professional's transition into data engineering by mastering Docker fundamentals and best practices. It covers key aspects such as Docker setup, container security, resource management, and the use of Docker Compose for production-ready environments. It also highlights the importance of secure configuration and iteration in system design, using real-world examples of data pipeline implementation and containerization strategies.  
21
3. 3  
[](https://daily.dev/posts/building-etl-pipeline-using-google-cloud-storage-7ynwfcqnh "Building ETL pipeline using Google Cloud Storage")  
Article  
![Avatar of detlife](https://media.daily.dev/image/upload/s--8lmPEq7G--/f_auto/v1725038518/logos/detlife)Data Engineer Things · 1y  
Building ETL pipeline using Google Cloud Storage  
The post provides a guide on creating a simple ETL pipeline using Google Cloud Storage to process Zomato restaurant data from Kaggle. It involves extracting, transforming, and loading the data using Python and Google Cloud Storage, offering insights suitable for beginners in data engineering. Key improvements include automation, extension to other cloud services, dashboarding, and data validation.  
10

[See all Data Engineer Things archives](/sources/detlife/best-of)

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