Getting Started

Start your data engineering journey by learning the fundamentals of modern data platforms, distributed systems, cloud data services, and the essential tools used to build scalable data pipelines.

Data Foundations

Build a solid understanding of data engineering fundamentals, including batch and stream processing, distributed computing, data storage, ETL/ELT, data modeling, and modern analytics architectures.

Data Processing

Learn how to process large-scale datasets using Apache Spark, SQL, distributed computing techniques, performance optimization, and production-ready batch data pipelines.

Data Streaming

Master real-time data processing with Apache Kafka, Apache Flink, Spark Structured Streaming, event-driven architectures, CDC pipelines, and scalable streaming systems.

Data Architecture

Design modern data platforms using lakehouse architectures, data lakes, data warehouses, cloud-native services, data governance, observability, and enterprise-scale reference architectures.

Data Interview

Prepare for data engineering and big data interviews with practical technical questions, Spark and Kafka concepts, distributed systems, architecture design scenarios, SQL, and senior-level interview strategies.