Customer Reliability Engineer (Airflow)

• 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
• 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 24x7 coverage through a specified 6-hour pager period during your work day
• Participate in paid on-call rotation for weekend coverage

Benefits

• Remote friendly, work from anywhere
• If you’re in a city with an office, it’s there (and stocked with snacks) when you need it
• Co-workers in over 40 states and 15 countries around the world
• Health, dental, and vision insurance at little to no cost for individuals, and at competitive rates for your dependents
• Disability and life insurance policies in case something happens
• Unlimited vacation - we do track vacation days and actively encourage people to take it (on average, Astronomers take 20 days of vacation per year)
• Parental leave
• Laptop of your choice, and a stipend to help with your work-from-home setup
• Monthly $170 pre-tax stipend intended to cover your cellphone and WiFi bills
• Yearly internal summit for all employees
• Regular access to conferences, workshops, and meetups in the ecosystem- 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
• Data Engineering background
• Strong written and verbal communication for connecting with our customers over our ticketing system and through Zoom
• 1 year of experience in Airflow administration and DAG creation
• Problem-solving and troubleshooting abilities
• 4 years of experience with Python
• Ability to work well with autonomy and independence
• Experience working with a distributed system with any major cloud provider (AWS, GCP, Azure)
• Experience with Kubernetes/Docker/Containers
• Experience mentoring junior team members
• 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