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Airflow Platform Engineer

Jade Global
Hyderabad, IND
Full-time
Mid · 4–6 years experience
Onsite
Discovered 3 weeks ago
airflowazuredbtdockergitjenkins

Full Job Posting

Experience

  • 4 - 6 years
  • Strong experience with Apache Airflow (3.x or later) in production environments
  • Proven experience in DAG development using operators and orchestration patterns
  • 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

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.
  • Working knowledge of Kubernetes (AKS preferred) to support Airflow runtime

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