Course curriculum
Stage 1
Foundations
- 1180 min
SQL Mastery
- 2180 min
Data Modeling Fundamentals
- 3
A 50-hour curriculum for data engineers ready to operate at senior+ levels at Snowflake-, Databricks-, and BigQuery-shop scale. You will build production-grade ELT pipelines with dbt-core 1.8+, design lakehouse architectures on Iceberg 1.4+ / Delta Lake 3.x, run sub-second streaming with Kafka 3.7+ and Flink 1.19, and operationalize data quality with Great Expectations, Soda, and data contracts. Outcome: you can rebuild a 100 TB warehouse from scratch, justify every tool choice with cost numbers, and pass senior data engineering loops at Stripe, Airbnb, Lyft, Shopify, and Netflix.
SQL Mastery
Data Modeling Fundamentals
Python for Data Engineering
ETL/ELT Pipeline Patterns
Workflow Orchestration with Airflow
Data Transformations with dbt
Data Quality & Testing
Dimensional Modeling & Star Schemas
Cloud Data Warehouses
Data Lake Architecture
Data Governance & Cataloging
Lakehouse Architecture (Iceberg, Delta, Hudi)
Real-Time Analytics & Streaming SQL
Apache Spark Deep Dive
Apache Kafka & Event Streaming
Streaming vs Batch Processing
Data Contracts & Schema Evolution
Interview Preparation for Data Engineers
CI/CD for Data Pipelines
Pipeline Monitoring & Observability
Data Mesh & Decentralized Architecture
System Design & Technical Leadership
Data Platform Cost Optimization