🗄️ Learning path

Data Engineering

Build batch and streaming data pipelines, search, and warehousing at scale.

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Data engineers move, transform, and serve data reliably at scale. This path takes
you from SQL ETL pipelines through real-time streaming with Apache Kafka, full-text
search and analytics with Elasticsearch, data lake architectures, and data quality
and observability - the end-to-end toolkit of a modern data platform.

What you'll learn

  1. 1. Building a SQL ETL Pipeline 🧪 Lab · 3 steps · 🔒 Subscriber ○
  2. 2. Kafka CLI Basics 🧪 Lab · 3 steps · 🔒 Subscriber ○
  3. 3. Kafka Java Producer API 🧪 Lab · 3 steps · 🔒 Subscriber ○
  4. 4. Kafka Streams Stateless Transformations 🧪 Lab · 3 steps · 🔒 Subscriber ○
  5. 5. Streaming ETL with Kafka 🧪 Lab · 3 steps · 🔒 Subscriber ○
  6. 6. Advanced Kafka Clustering 🧪 Lab · 3 steps · 🔒 Subscriber ○
  7. 7. Elasticsearch & Kibana Deep Dive 🧪 Lab · 7 steps · 🔒 Subscriber ○
  8. 8. Data Lake Architectures 🧪 Lab · 3 steps · 🔒 Subscriber ○
  9. 9. Data Quality & Observability 🧪 Lab · 3 steps · 🔒 Subscriber ○
  10. 10. Chunking & Ingestion for RAG 🧪 Lab · 3 steps · 🔒 Subscriber ○
  11. 11. Distributed Embedding at Scale 🧪 Lab · 3 steps · 🔒 Subscriber ○
  12. 12. Data Engineering - Knowledge Check ❓ Quiz · 🔒 Subscriber ○