A comprehensive collection of data engineering learning materials, notes, projects, hands-on examples, interview preparation, and real-world implementations covering modern data platforms, big data, streaming, lakehouse, cloud, and data engineering tools.
| Section | Topics |
|---|---|
| 01-Fundamentals | SQL, Python, Data Structures, Linux, Git, Docker, Kubernetes, MongoDB |
| 02-Big-Data | Hadoop, Spark, Hive |
| 03-Data-Streaming | Kafka, Debezium, CDC |
| 04-Data-Lakehouse | Iceberg, Hudi, Delta Lake, Trino |
| 05-Orchestration | Airflow, Dagster |
| 06-Transformation | dbt |
| 07-Cloud | AWS, GCP, Azure |
| 08-Data-Quality | Great Expectations, Data Validation |
| 09-Projects | Batch, Streaming, Lakehouse, and CDC pipelines |
| 10-System-Design | Data pipeline, lakehouse, and streaming architecture |
| 11-Interview-Preparation | SQL, Python, Spark, Kafka, Hive, Java, LeetCode, Data Engineering, System Design |
| 12-Notes | General notes |
| 13-Software-Engineering | Java, Spring, Hibernate, HTML |
| resources | Books, Courses, Blogs, YouTube, Open-Source Tools |