Job Overview
Location
Remote (United States)
Job Type
Full-time
Category
Data Science
Date Posted
June 26, 2026
Full Job Description
đź“‹ Description
- • Serve as an Apache Airflow expert on the Customer Reliability Engineering (CRE) team, providing direct technical support to enterprise customers using Astronomer’s managed Airflow platform.
- • Diagnose and resolve complex Airflow issues ranging from DAG optimization to identifying previously unknown bugs in the Apache Airflow codebase.
- • Collaborate with customers’ data engineers, DevOps teams, and system administrators to ensure mission-critical data pipelines run reliably and efficiently.
- • Deliver “white glove” customer guidance through ticketing systems and Zoom calls, prioritizing issues, meeting SLAs, and guiding customers to production readiness.
- • Gain deep expertise across software engineering domains including Kubernetes, cloud infrastructure (AWS, GCP, Azure), and data engineering practices.
- • Contribute up to 20% of your time to internal side projects such as enhancing Astronomer’s monitoring systems or submitting patches to the open-source Apache Airflow repository.
- • Participate in a 24x7 on-call rotation with a specified 6-hour pager window during your workday and additional paid weekend coverage.
- • Work within a fully distributed, remote-first team while maintaining high standards of customer empathy and technical precision.
- • Translate customer feedback into actionable insights that influence the future direction of the Apache Airflow project and Astronomer’s product roadmap.
- • Engage directly with customers to understand their operational challenges, interpret their needs, and deliver tailored solutions that align with their technical environments.
- • Learn from and collaborate with leaders of the Apache Airflow project to deepen your understanding of the platform’s architecture and evolution.
- • Balance autonomy with accountability, independently managing your workload while ensuring consistent, high-quality customer outcomes.
- • Communicate complex technical concepts clearly and effectively in writing and verbally to diverse audiences including non-technical stakeholders.
- • Mentor junior team members and contribute to a culture of knowledge sharing and continuous learning.
- • Work on a cloud-native, enterprise-grade DataOps platform that integrates with dozens of data systems and supports AI and analytics workloads at scale.
🎯 Requirements
- • Data Engineering background
- • 4 years of experience with Python
- • 1 year of experience in Airflow administration and DAG creation
- • Experience with Kubernetes/Docker/Containers
- • Experience working with a distributed system with any major cloud provider (AWS, GCP, Azure)
- • Problem-solving and troubleshooting abilities
🏖️ Benefits
- • Paid on-call rotation for weekend coverage
- • Equity component as part of total compensation
- • Comprehensive benefits package
- • Estimated total compensation range of $125,000 - $130,000
- • Opportunity to contribute to open-source Apache Airflow
- • Work in a fully distributed, remote-first team
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Astronomer, Inc.
Astronomer, Inc. provides Apache Airflow as a managed cloud service and enterprise platform. The company maintains the open-source workflow orchestration project, offers commercial support, and delivers a control plane that lets data teams deploy, monitor, and scale directed acyclic graphs across Kubernetes clusters. Its product suite includes Astro, a fully hosted Airflow environment with role-based access, CI/CD hooks, and usage observability. Customers use the software to schedule Python and SQL data pipelines, connect on-premise and cloud databases, and ensure reliable data delivery for analytics and machine-learning workloads. Astronomer is headquartered in Cincinnati, Ohio, and serves global enterprises.
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