Airflow Platform Engineer
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Before you apply
LocationHyderabad, Telangana; Pune, Maharashtra
Typefull-time
SeniorityMid
Experience4–6 yrs
Company size1,001–5,000 people
PostedJun 30, 2026 · 4mo ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
4-6 years of experience
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
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
Skills
Apache Airflow
Python
Kubernetes
AKS
Azure
DBT
Git
Jenkins
Docker
Snowflake
Splunk
Prometheus
Azure Key Vault
Airflow Platform Engineer1
Experience - 4 - 6 years
Responsibilities
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
Requirements
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
Nice to have
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
About the role
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.