Sales Engineer
Astronomer1 month ago
Responsibilities
- Lead technical sales activities with Account Executives, including discovery, demos, proof-of-concepts, and architecture discussions.
- Translate customer pain points into high-impact technical solutions tied to business value.
- Build and deliver tailored demos and proof-of-concepts using Python, Airflow, and related tools.
- Guide customers on DataOps strategies spanning orchestration, observability, and automation.
- Influence product feedback loops, collaborate cross-functionally, and contribute to go-to-market strategy.
Requirements
- Fluency in Python, comfort with command-line interfaces, and experience with tools such as Docker.
- Familiarity with cloud-native data architectures on AWS, GCP, or Azure.
- Understanding of orchestration, ELT/ETL, DAGs, and CI/CD workflows.
- Exposure to Airflow, Snowflake, Databricks, BigQuery, dbt, or similar platforms.
- Three to ten years of total experience, including at least two years in a customer-facing technical role such as Sales Engineering or Solutions Architecture.
- Strong communication skills across technical and business stakeholders.
- Experience with observability, Kubernetes, or scaling modern data stacks is preferred.
Benefits
- Approximately 25% regional travel is required, with about two days per week in the office or at customer meetings.
- Candidates should be within reasonable commuting distance of New York City.
- The role includes an equity component in addition to compensation.
- Astronomer is an equal opportunity employer committed to diversity.
Tech Stack
Apache AirflowAstroAWSAzureDatabricksdbtDockerGoogle BigQueryGoogle Cloud PlatformKubernetesPythonSnowflake
Categories
Solutions Engineering
About Astronomer
Astronomer builds Astro, a data orchestration platform powered by Apache Airflow that lets data teams run, monitor, and govern complex pipelines across clouds. It sells managed Airflow and enterprise tooling via subscriptions, backed by expert support and services. Founded in 2018 and headquartered in New York, the privately held company focuses on enterprises operationalizing analytics and AI workloads.