Airflow Platform Engineer

Airflow Platform Engineer1 Experience - 4 - 6 years

• Key Responsibilities
• DAG Development & Developer Enablement
• •Design, develop, and optimize Airflow DAGs for enterprise use cases
• •Demonstrate strong experience with operators such as PythonOperator, SQL operators,
• API/HTTP operators, KubernetesPodOperator etc.
• •Apply advanced DAG patterns including dynamic DAGs, branching, sensors, retries, and
• error handling
• •Troubleshoot DAG failures, performance issues, and integration challenges
• •Enable orchestration of modern data workflows including DBT pipelines
• •Provide reusable templates, best practices, and onboarding support to drive self-service
• adoption
• Platform Operations & Kubernetes Support
• •Support Airflow platform deployed on AKS, covering scheduler, webserver/API, workers,
• and metadata services
• •Troubleshoot issues related to task execution, scheduling delays, and resource bottlenecks
• •Diagnose Kubernetes-level issues involving pods, networking, storage, and RBAC
• •Work with Azure services such as Key Vault, Storage, and networking
• •Support CI/CD pipelines for DAG and container-based deployments
• •Improve platform stability, monitoring, and alerting

• Required Skills
• •Strong experience with Apache Airflow (3.x or later) in production environments
• •Proven experience in DAG development using operators and orchestration patterns
• •Working knowledge of Kubernetes (AKS preferred) to support Airflow runtime

• •Expert-level Python knowledge for building, debugging, and maintaining production-
• grade workflows and supporting libraries
• •Expertise in writing unit, integration, and DAG validation tests for Airflow workflows,
• including mocking operators, validating dependencies, and ensuring reliability in CI/CD
• pipelines
• •Experience with DBT and modern data pipelines
• •Experience with CI/CD tools (Git, Jenkins, Docker)
• •Familiarity with Azure or other cloud platforms

• Preferred Skills
• •Experience with Astronomer / Astro Private Cloud
• •Exposure to data platforms such as Snowflake, and APIs
• •Experience with monitoring tools such as Splunk or Prometheus
• •Knowledge of secrets management using Azure Key Vault

• Summary
• This role is critical to ensuring reliable platform operations and scalable adoption of the
• Airflow-based orchestration platform. The ideal candidate combines strong Airflow
• expertise, Kubernetes knowledge, and hands-on development experience to support both
• platform stability and developer productivity.