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Mid-level metro role with niche Airflow/Kubernetes specialization, moderating applicant density.
Platform and Airflow expertise is transferable across industries but remains fairly domain-specific.
Explicit 4–6 years plus mandatory Airflow, Kubernetes, Python, CI/CD requirements increase screening rigidity.
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Design, develop, and optimize Airflow DAGs with advanced patterns and operators for enterprise workflows.
Support and troubleshoot Airflow platform on AKS including scheduler, webserver/API, workers, and metadata services, ensuring platform stability.
Work with Kubernetes, Azure services, and CI/CD pipelines to maintain and improve orchestrated data workflows including DBT pipelines.
4 - 6 years of relevant work experience.
Strong experience with Apache Airflow (3.x or later) in production environments and DAG development expertise.
Proficient in Kubernetes (AKS preferred) and expert-level Python for production-grade workflow development.
Experience with CI/CD tools (Git, Jenkins, Docker) and familiarity with Azure cloud services.
Experienced in handling production Airflow environments combining platform operations and developer enablement roles.
Skilled in troubleshooting at both workflow level (DAGs) and infrastructure level (Kubernetes, Azure services).
Comfortable working in cloud-native environments integrating Airflow with modern data pipelines such as DBT and leveraging CI/CD practices for workflow reliability.