Airflow

Apache Airflow has become the de facto standard for orchestrating complex data pipelines in modern data engineering workflows. Originally developed at Airbnb, Airflow allows teams to programmatically author, schedule, and monitor workflows as directed acyclic graphs (DAGs) using Python code. Its appearance in job listings typically signals organizations with mature data infrastructure that need to coordinate dependencies between ETL jobs, machine learning model training, and business intelligence updates. Data engineers are expected to design resilient pipelines with proper retry logic, monitoring, and alerting. The platform's extensibility through custom operators and hooks makes it particularly valuable for companies integrating diverse data sources and processing frameworks. Roles requiring Airflow experience often involve building and maintaining production data platforms that power analytics, reporting, and machine learning systems across the organization.