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Data Engineering is the backbone of AI and Analytics. If you want to move from “learning to code” to “building production-grade systems,” you need a clear path. Swipe through to learn: ✅ What a Data Engineer actually does. ✅ The 5 stages of the Data Lifecycle: Generation ➡️ Ingestion ➡️ Storage ➡️ Transformation ➡️ Serving. ✅ The must-know Cloud stack (AWS, Azure, GCP). ✅ DSA topics specifically for Data Engineers. Don’t just collect tools; understand the architecture. Ready to start? Drop a “DE ROADMAP” in the comments for the full guide!