Apache Airflow Interview Questions: Data Orchestration Deep Dive
Everything you need to know about Airflow for data engineering interviews — DAGs, operators, scheduling, best practices, and common gotchas.
Key Takeaways
- ✓Airflow in the Modern Data Stack
- ✓Core Concepts to Know
- ✓Advanced Topics
Airflow in the Modern Data Stack
Apache Airflow is the most popular data orchestration tool. If a company uses Python-based data pipelines, they almost certainly use Airflow (or a managed version like Cloud Composer or MWAA).
Expect Airflow questions in any company that values pipeline reliability and observability.
Core Concepts to Know
- DAGs, operators, and tasks
- Sensors and their use cases
- XComs for task communication
- Connections and hooks
- Executor types (Local, Celery, Kubernetes)
- Trigger rules and branching
- Backfill and catchup behavior
Advanced Topics
For senior roles:
- Dynamic DAG generation patterns
- Custom operators and plugins
- Airflow 2.x TaskFlow API
- Scaling Airflow (KubernetesExecutor, auto-scaling workers)
- Monitoring and alerting strategies
- CI/CD for DAGs
Written by the DataEngPrep Team
Our editorial team consists of experienced data engineers who have worked at top tech companies and gone through hundreds of real interviews. Every article is reviewed for technical accuracy and practical relevance to help you prepare effectively.
Learn more about our team →Related Articles
Practice These Questions
Ace Your Interview with AI Coaching
1,800+ expert answers, AI mock interviews, and personalized feedback to get you hired.