Sales Engineer, EMEA
AI in this role
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:
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. As a Sales Engineer at Astronomer, you’ll be a key partner to our prospects and customers, guiding them in deploying powerful data workflows to accelerate their business outcomes. You'll work with cutting-edge technology, help customers solve complex data challenges, and have a voice in influencing our product’s evolution through client feedback. This role is ideal for someone who wants to make a visible impact while growing into an expert in workflow orchestration and Apache Airflow.
✈️ Location: The position is based in London but requires regular travel to France, 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-obsessed, 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 would possess:
Business level French language skills
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, ELT/ETL, DAGs, CI/CD
Exposure to platforms like Airflow, Snowflake, Databricks, BigQuery, dbt, or similar
3–10 years total experience, including 2+ years in a customer-facing technical role (Sales Engineering, Solutions Architect, etc.)
Strong communication skills across technical and business stakeholders
Startup-friendly mindset: proactive, adaptable, fast-moving
⭐️ Bonus points if you have:
Experience with observability, Kubernetes, or helping teams scale modern data stacks.
Why Astronomer?
We’re defining the DataOps layer of the modern data stack - not just orchestration
Airflow is the standard - we’re making it enterprise-ready, secure, and scalable
Backed by top-tier investors and trusted by data-forward organizations
You’ll work with a team that values clarity, ownership, and high standards - without ego
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.
How we rate this
Sales Engineer, EMEA at Astronomer rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used Databricks hands-on?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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