Customer Reliability Engineer, Airflow

Remote from: USA
Salary, yearly, USD: 125,000 - 130,000
Department: Technical Support
Employment type: Full Time,
Job posted: 25 Jun 2026
Apply before: 25 Jul 2026
Views / Applies: 88 / 6

About company

About Astronomer

The Apache Airflow Company

Computer Software
2015

Actively Hiring

AI Summary

Astronomer is seeking a Customer Reliability Engineer to provide expert support for their Apache Airflow platform. This role involves solving complex Airflow problems, working directly with customers, and contributing to the open-source Airflow project. The ideal candidate has a data engineering background, strong Python skills, and experience with Kubernetes and cloud providers. The position offers a salary range of $125,000-$130,000, plus equity and benefits.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role requires deep technical expertise in Airflow, Kubernetes, and Python, along with strong problem-solving and customer-facing skills, making it challenging but not the hardest.

Salary Analysis

AI Insight The offered salary of $125,000-$130,000 is competitive for a Customer Reliability Engineer with this level of expertise, falling within the typical market range for similar roles in the US.

Key Skills

Apache Airflow Kubernetes Python Data Engineering Customer Support Cloud Computing Docker Troubleshooting DevOps Open Source

Cover Letter Sample

I am excited to apply for the Customer Reliability Engineer position at Astronomer. With a strong background in data engineering and over four years of Python experience, I have developed deep expertise in Apache Airflow and Kubernetes that aligns perfectly with your requirements.

In my previous role, I successfully managed Airflow deployments and provided technical support to clients, ensuring high availability and performance. I am passionate about solving complex problems and thrive in fast-paced, collaborative environments.

I am particularly drawn to Astronomer's commitment to open-source and the opportunity to work directly with the creators of Airflow. I look forward to contributing to your team and helping customers achieve their data pipeline goals.

Possible Interview Questions

Can you describe your experience with Apache Airflow, including any complex deployments or issues you have resolved?

I have over two years of experience with Airflow, including managing multi-cluster deployments and optimizing DAG performance. For example, I resolved a deadlock issue by refactoring task dependencies and adjusting pool configurations.

How do you approach troubleshooting a customer's Airflow issue when the root cause is not immediately obvious?

I start by gathering detailed logs and metrics, then reproduce the issue in a test environment. I systematically check common failure points like resource constraints, connection errors, and code bugs, and escalate to the engineering team if needed.

Describe a time you had to balance multiple high-priority support tickets. How did you manage your time?

I prioritize tickets based on severity and SLA requirements, communicate transparently with customers about expected timelines, and use automated alerts to stay on top of urgent issues. I also collaborate with team members to share the workload.

What is your experience with Kubernetes and how have you used it in a data engineering context?

I have deployed and managed Airflow on Kubernetes using Helm charts, configured autoscaling for worker pods, and integrated with cloud providers for storage and networking. I also troubleshoot pod failures and optimize resource requests.

How do you handle a situation where a customer disagrees with your technical recommendation?

I listen to their perspective and explain the reasoning behind my recommendation, providing data and examples. If they still disagree, I explore alternative solutions that meet their needs while ensuring reliability, and involve a senior engineer if necessary.

Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading unified DataOps platform powered by Apache Airflow®. Astro accelerates building reliable data products that unlock insights, unleash AI value, and powers data-driven applications. Trusted by more than 800 of the world’s leading enterprises, Astronomer lets businesses do more with their data. To learn more, visit www.astronomer.io.

About this role:

As an Airflow Reliability Engineer on the Customer Reliability Engineering (CRE) team at Astronomer, you will have the opportunity to become an Apache Airflow expert, learning directly from leaders of the Airflow project. You’ll provide Apache Airflow expertise directly to customers to help them make the best possible use of our managed Airflow service.

CRE is Astronomer’s support team. Because our customers are sophisticated organizations who need and expect high levels of expertise to help them keep mission critical uses of Apache Airflow working consistently, we look a little different from most support teams. Nearly every ticket you will work requires an intersection of strong technical knowledge and customer empathy to understand what the customer needs and how to get them there. Every day is a new challenge and a new thing to learn.

When you learn a new piece of technology, are you aiming not just to get started but to become the expert? Do you listen to the plumber when they tell you what is wrong with the pipes? Are you the kind of person who takes an MIT OpenCourseWare course and actually finishes it? Then this role could be for you.

What you get to do:

Learn and build expertise across several software engineering disciplines, including:
Airflow and data engineering
Kubernetes
Cloud Engineering
Gain exposure to the big picture; learn about product, engineering, customer relationship management, and more.
Solve challenging Airflow problems for our customers. From optimizing configuration to identifying world-first Airflow bugs, you’ll see it all here.
Spend up to 20% of your time on side projects that contribute to Astronomer’s overall success, such as contributing to the open-source Airflow repository or developing Astronomer’s internal monitoring and alerting systems built on Airflow.
Work on a modern, sophisticated, cloud-native product that customers use to connect to dozens of other systems. Gain depth and breadth of learning!
Work directly with our customers’ data engineers, system admins, DevOps teams, and management.
Provide feedback from your experience that can shape the direction of the Airflow project.
Own the customer experience, working directly with customers to prioritize and solve issues, meet SLAs, and provide “white glove” guidance on the path to production.
Participate remotely within a fully distributed team.
Help maintain 24×7 coverage through a specified 6-hour pager period during your work day.
Participate in paid on-call rotation for weekend coverage.

What you bring to the role:

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
Ability to work well with autonomy and independence
Strong written and verbal communication for connecting with our customers over our ticketing system and through Zoom
Experience mentoring junior team members

Bonus points if you have:

Contributions to open-source projects
Customer Support experience
Familiarity with SQL and PostgreSQL
Experience with Databricks, Snowflake, Redshift, dbt, or other similar data engineering tools

The estimated total compensation for this role ranges from $125,000 – $130,000 based on leveling and geography, along with an equity component and a comprehensive benefits package. This range is merely an estimate; actual compensation may deviate from this range based on skills, experience, and qualifications.

#LI-Fulltime

#LI-Remote

At Astronomer, we value diversity. We are an equal opportunity employer: we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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