Data Engineering

A book-shaped table of contents for data engineering: foundations and lifecycle, data modeling, storage systems, ingestion and CDC, distributed processing (Spark/Flink), SQL mastery, workflow orchestration, data quality, platform and cloud architecture, pipeline observability, security and governance, performance engineering, system design, and MAANG interview preparation through capstone builds — cross-linking the existing observability book instead of duplicating it.

1 — Batch Processing System Design

Open-ended batch processing system design — log analytics platforms, ETL platforms, and reporting pipelines.

3 — Data Lakehouse Design

Designing a lakehouse end to end — bronze/silver/gold layering, incremental pipeline design, and cross-team data sharing.

4 — ML Data Platform Design

Designing the data platform underneath ML systems — feature stores, offline and online stores, and the pipelines that feed model training and serving.

Data Engineering

A book-shaped table of contents for data engineering: foundations and lifecycle, data modeling, storage systems, ingestion and CDC, distributed processing (Spark/Flink), SQL mastery, workflow orchestration, data quality, platform and cloud architecture, pipeline observability, security and governance, performance engineering, system design, and MAANG interview preparation through capstone builds — cross-linking the existing observability book instead of duplicating it.