Apache Airflow
Master data pipeline orchestration with the industry-standard workflow management platform. Build reliable, scalable, and monitored data pipelines that actually work.
What You'll Master
- DAG (Directed Acyclic Graph) fundamentals and best practices
- Core operators: PythonOperator, BashOperator, SQL operators
- Advanced concepts: Sensors, XComs, and custom operators
- Error handling, retries, and monitoring strategies
- Production deployment and scaling considerations
- Integration with cloud platforms (AWS, GCP, Azure)
- Real-world pipeline patterns and troubleshooting
- Performance optimization and best practices
Course Structure
- Module 1: Airflow Fundamentals - Understanding DAGs and Operators
- Module 2: Building Your First Pipeline - From Hello World to Real ETL
- Module 3: Advanced Patterns - Sensors, XComs, and Custom Components
- Module 4: Production Ready - Deployment, Monitoring, and Scaling
- Module 5: Real-World Projects - End-to-End Pipeline Development
Prerequisites
- Basic Python programming knowledge
- Understanding of data pipelines and ETL concepts
- Familiarity with command line and basic DevOps concepts
- Experience with databases (SQL) is helpful but not required
Career Opportunities
- Data Engineer: $95,000 - $150,000+ (Airflow is essential)
- DevOps Engineer: $90,000 - $140,000+ (Workflow automation)
- Platform Engineer: $100,000 - $160,000+ (Infrastructure automation)
- ML Engineer: $110,000 - $170,000+ (ML pipeline orchestration)
- Solutions Architect: $120,000 - $180,000+ (System design)
Ready to Stop Fighting Pipeline Fires?
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