Foundations of Data Engineering (5 days):

• Relational Databases (e.g., PostgreSQL, MySQL, Oracle, SQL Server)
• SQL
• Data Modelling
• Indexing and optimization

Data Warehousing and ETL Tools (5 days):

• Cloud Data Warehouses (e.g., AWS Redshift, Google BigQuery, Azure Synapse Analytics)
• Modern Data Integration Tools (e.g., Apache Airflow)
• Informatica PowerCenter or ETL Tools

Distributed Computing and Big Data Technologies (5 days):

• Apache Hadoop
• Apache Kafka
• Apache Flink
• Apache Spark
• Data streaming architectures

Data Governance and Security (5 days):

• Apache Atlas
• Data privacy regulations
• Data security

Advanced Data Engineering Concepts (5 days):

• Apache Spark: 2 days
• Change Data Capture (CDC): 2 days
• Data streaming architectures: 1 day

Cloud Data Platforms and Serverless Computing (5 days):

• AWS Data Lake
• Google Cloud BigQuery or Azure Data Factory or AWS Redshift
• Snowflake
• Databricks

Patterns:

• Lambda Architecture
• Data Warehousing Patterns (dimensional modeling, star schema, snowflake schema)
• Event-Driven Architecture (event sourcing, CQRS, message brokers)
• Microservices Architecture (bounded contexts, domain-driven design, API-first)
• Data Streaming Patterns (event-driven streaming, windowing, time-based aggregations)