Airflow Reliability Engineer

Astronomer is seeking an Airflow Reliability Engineer to join their Customer Reliability Engineering (CRE) team. This role offers a unique opportunity to become an Apache Airflow expert while working directly with customers on their managed Airflow service. The position combines deep technical expertise with customer-facing support, requiring both strong engineering skills and excellent communication abilities.

As part of Astronomer's sophisticated support team, you'll tackle complex technical challenges daily, working with mission-critical Apache Airflow implementations. The role involves not just troubleshooting and optimization, but also contributing to the broader Airflow ecosystem and Astronomer's internal systems.

The ideal candidate brings 4+ years of professional experience with strong Python skills and expertise in cloud technologies and Kubernetes. You'll work in a fully distributed team environment, providing high-level support to sophisticated organizations while having the opportunity to shape the direction of the Airflow project.

Key responsibilities include providing expert Airflow guidance, solving complex configuration issues, contributing to open-source projects, and maintaining platform reliability. You'll also have the opportunity to work on side projects that contribute to Astronomer's success, spending up to 25% of your time on these initiatives.

The role offers competitive compensation ($130,000-$160,000) with equity, and provides exposure to cutting-edge data engineering technologies and practices. You'll work with a globally-distributed team of innovators and collaborators, contributing to Astronomer's mission of empowering data teams to bring mission-critical analytics, AI, and software to life.

This position is ideal for someone who is passionate about becoming an expert in their field, enjoys solving complex technical challenges, and wants to work at the intersection of customer support and advanced technology. The role offers significant growth potential and the opportunity to work with leading organizations in the data engineering space.