Airflow Platform Engineer
Jade Global Open · verified Oct 24, 2026 At a glance
Mid-level Platform & Infrastructure role at Jade Global. Hyderabad · full-time.
Pay not stated Platform Engineer salary
devopsroles summary, based on the employer's posting.
What you'll do
- Build and tune production Airflow DAGs, using operators and patterns such as branching, sensors, retries and dynamic workflows
- Diagnose failed tasks, slow scheduling, performance problems and integrations across Airflow workflows
- Support Airflow services running on AKS, including workers, schedulers, web interfaces and metadata components
- Investigate Kubernetes issues with pods, networking, storage and access controls, and work with Azure services
- Create reusable DAG guidance and onboarding, support CI/CD releases, and strengthen platform monitoring and alerting
What you bring
- Four to six years of experience, with hands-on Apache Airflow use in production environments
- Strong Python skills for developing and debugging production workflows, libraries and Airflow tests
- Experience building DAGs with operators and orchestration patterns, plus working knowledge of Kubernetes
- Experience with DBT pipelines and CI/CD tools such as Git, Jenkins or Docker
Who this fits
This mid-level role suits an engineer who can combine Airflow development with Kubernetes platform support and workflow testing. The position is based in Hyderabad, India.
From the employer
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.
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