Astronomer

Tech / AI / Software

SalesEngineer

$200–250k Washington, District of Columbia, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Sales Engineer at Astronomer. Skills: Sales Engineering, DataOps, Apache Airflow. Lead the technical sales motion in partnership with Account Executives. discovery”

What You'll Achieve.

bring mission-critical software, analytics, and AI to life; accelerates building reliable data products that unlock insights, unleash AI value, and powers data-driven applications; make DataOps a first-class discipline in every modern data organization; powering mission-critical pipelines at scale; orchestrate, observe, and optimize their data pipelines with confidence

Industry & Context.

Tech / AI / Software
Problems you'll solve

solving real problems with data teams

Eligibility Requirements

regional travel of approximately 25%

What They're Looking For.

Must Have

Python fluency, CLI comfort, experience building with tools like Docker, Familiarity with cloud-native data architectures (AWS, GCP, or Azure), Understanding of data engineering workflows: orchestration, ELT/ETL, DAGs, CI/CD, Exposure to platforms like Airflow, Snowflake, Databricks, BigQuery, dbt, or similar, 3–10 years total experience, 2+ years in a customer-facing technical role (Sales Engineering, Solutions Architect, etc.), communication skills across technical and business stakeholders, Startup-friendly mindset: proactive, adaptable, fast-moving

Nice to Have

Experience with observability, Kubernetes, helping teams scale modern data stacks

What You'll Do.

Lead the technical sales motion in partnership with Account Executives

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

Guide customers through modern DataOps strategies - from orchestration to observability and automation

Influence product feedback loops

contribute to go-to-market strategy

How You'll Work.

Team & Collaboration

partnership with Account Executives; collaborate cross-functionally

Communication Scope

communication skills across technical and business stakeholders

Full Job Description

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 http://www.astronomer.io. ABOUT THIS ROLE: 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. The position requires regional travel of approximately 25%, aligned with business needs. What You Get to Do: - 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 What you bring to the role: 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 - Familiarity with cloud-native data architectures (AWS, GCP, or Azure) - Understanding of data engineering workflows: orchestration,

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