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@Lutschippi Awesome resource. Finding a centralized, up-to-date guide for core pipeline concepts and analytical patterns without getting bogged down in tool hype is rare. Appreciate you keeping this free and open source!
The data engineering space moves FAST.
Spark, dbt, Kafka, Flink, Iceberg, Delta Lake, duckdb, Airflow, Dagster — new tools drop every quarter and the learning curve never ends.
So I built https://t.co/afqWSBV3Sf — a focused, up-to-date reference that cuts through the noise and covers what you actually need to know:
✅ Core pipeline concepts
✅ SQL & analytical query patterns
✅ Streaming fundamentals
✅ Warehouse & lakehouse architecture
✅ Interactive quiz to test your knowledge
100% free. 100% open source.
Bookmark it now, thank yourself later → https://t.co/jAMzcz7Ftf
RT to help a fellow data engineer 🔁
Just shipped something I've been building for the data engineering community 🔧
Data Engineer Hub — your go-to reference for pipelines, SQL, streaming, and warehousing concepts. All in one place, no fluff.
And yes, there's an interactive quiz to test how sharp your DE skills actually are 🧠
Open source → https://t.co/Btf1sMuVjl
Drop a ⭐ if you find it useful. Building this in public. Feedback welcome.
Hot take: most data engineers learn 80% of their stack from scattered docs, random blog posts, and Stack Overflow at 2am.
So I built Data Engineer Hub — a focused knowledge base covering the stuff that actually matters on the job: pipelines, SQL patterns, streaming architecture, and warehouse design.
Free, open source, no login needed.
👉 https://t.co/Btf1sMuVjl
RT if you know someone breaking into data engineering 🔁
Think you know data engineering? 👀
I built a quiz that covers:
✅ Pipeline design
✅ SQL & query optimization
✅ Streaming vs batch
✅ Data warehouse patterns
Most people don't pass on the first try (not gonna lie, I designed it to be hard)
Try it free → https://t.co/Btf1sMuVjl
Drop your score below 👇