Data Architect, Professional Services - Remote

Overview

Astronomer designed Astro, an industry-leading, orchestration-first DataOps platform for data teams. Powered by Airflow, Astro accelerates building reliable data products that unlock insights, unleash AI value, and drive data-driven applications.

We’re a globally-distributed and rapidly growing venture-backed team of learners, innovators and collaborators. Our mission is to empower data teams to bring mission-critical analytics, AI, and software to life. As a member of our team, you will be at the forefront of the industry as we strive to deliver the world's data.

Your background may be unconventional; as long as you have the essential qualifications, we encourage you to apply. While having "bonus" qualifications makes for a strong candidate, Astronomer values diverse experiences. Many of us at Astronomer haven't followed traditional career paths, and we welcome it if yours hasn't either.

In Short

• Work directly with Astronomer customers, acting as technical lead for high-stakes professional services engagements
• Participate in pre-sales motions where a specialized technical solution is required
• Build architecture, data flow, and operational diagrams and documents
• Provide reference implementations of various activities, including composing data pipelines in Airflow, implementing new Airflow features, or integrating Airflow with 3rd party solutions
• Collaborate to build reusable assets, automation tools, and documented best practices
• Interact with Product and Engineering stakeholders to channel product feedback and requirements discussions
• Work with Global Service Delivery team members to ensure clients are realizing value in their Airflow and Astronomer journeys
• Establish strong relationships with key customer stakeholders

Requirements

• Experience with Apache Airflow in production environments
• Experience in designing and implementing ETL, Data Warehousing, and ML/AI/analytics use cases
• Experience with OpenLineage and data quality and observability tools
• Proficiency in Python and ideally other programming languages
• Knowledge of cloud-native data architecture
• Demonstrated technical leadership on team projects
• Strong oral and written communication skills
• Customer empathy
• Willingness to learn new technologies and build reference implementations

Benefits

• 7+ years experience in a data engineering or similar role
• 2+ years in a customer-facing role
• Consulting experience
• Experience in migrating workflows from legacy schedulers to Apache Airflow
• Snowflake experience
• Databricks or Spark experience
• Kubernetes experience, either on-premise or in the cloud
• Enterprise data experience in regulated environments