The ad says“Familiarity with cloud-native data architectures (AWS, GCP, or Azure)”
The ad says“Familiarity with cloud-native data architectures (AWS, GCP, or Azure)”
The ad says“Understanding of data engineering workflows: orchestration, ELT/ETL, DAGs, CI/CD”
The ad says“Python fluency, CLI comfort, and experience building with tools like Docker”
The ad says“Familiarity with cloud-native data architectures (AWS, GCP, or Azure)”
The ad says“Understanding of data engineering workflows: orchestration, ELT/ETL, DAGs, CI/CD”
The ad says“Python fluency, CLI comfort, and experience building with tools like Docker”
The ad says“Understanding of data engineering workflows: orchestration, ELT/ETL, DAGs, CI/CD”
The ad says“Familiarity with cloud-native data architectures (AWS, GCP, or Azure)”
The ad says“Understanding of data engineering workflows: orchestration, ELT/ETL, DAGs, CI/CD”
The ad says“Python fluency, CLI comfort, and experience building with tools like Docker”
Values
The ad says“Exposure to platforms like Airflow, Snowflake, Databricks, BigQuery, dbt, or similar”
The ad says“Exposure to platforms like Airflow, Snowflake, Databricks, BigQuery, dbt, or similar”
The ad says“Exposure to platforms like Airflow, Snowflake, Databricks, BigQuery, dbt, or similar”
The ad says“Exposure to platforms like Airflow, Snowflake, Databricks, BigQuery, dbt, or similar”
The ad says“Experience with observability, Kubernetes, or helping teams scale modern data stacks”
The ad says“Experience with observability, Kubernetes, or helping teams scale modern data stacks”
The ad says“Exposure to platforms like Airflow, Snowflake, Databricks, BigQuery, dbt, or similar”
Astronomer is on a mission to make DataOps a first-class discipline in every modern data organization
As the driving force behind Apache Airflow, we’re powering mission-critical pipelines at scale for companies like Condé Nast, Rappi, Sonos, and more. We’re expanding our Sales Engineering team to help data teams orchestrate, observe, and optimize their data pipelines with confidence
Lead the technical sales motion in partnership with Account Executives - discovery, demos, proof-of-concepts, and architecture discussions
Understand customer pain and translate it into high-impact technical solutions tied to business value
Build and deliver tailored demos and POCs using Python, Airflow, and related tools
Guide customers through modern DataOps strategies - from orchestration to observability and automation
Influence product feedback loops, collaborate cross-functionally, and contribute to go-to-market strategy
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
Preferred experience
You’re technically sharp, customer-oriented, and energized by solving real problems with data teams
We’re not looking for a perfect checklist match - but here’s what a strong candidate might bring:
Python fluency, CLI comfort, and experience building with tools like Docker
3–10 years total experience, including 2+ years in a customer-facing technical role (Sales Engineering, Solutions Architect, etc.)
Familiarity with cloud-native data architectures (AWS, GCP, or Azure)
Strong communication skills across technical and business stakeholders
Understanding of data engineering workflows: orchestration, ELT/ETL, DAGs, CI/CD
Exposure to platforms like Airflow, Snowflake, Databricks, BigQuery, dbt, or similar
