Astronomer Airflow Architect

The role:

The Solutions Architect specializing in Cloud Orchestration, will work with a small group of technologists and become a trusted advisor delivering technical solutions leveraging Apache Airflow hosted on the Astronomer platform. In this role, he will engineer a wide range of use cases where, Apache Airflow sits at the center of the solution, with the goal of rapidly developing solutions for the use cases.

• Help guide a small group of technologists in their Apache Airflow journeys, including identifying new use cases and onboarding new domain teams.
• Review, optimize, and tune data ingestion and extraction pipelines orchestrated by Airflow.
• Development of frameworks to manage and engineer a large number of pipelines for the entire domain.
• Build architecture, data flow, and operational diagrams and documents, with detailed physical and logical layers.
• Provide reference implementations of various activities, including composing data pipelines in Airflow, implementing new Airflow features, or integrating Airflow with 3rd party solutions.
• Keep up with the latest Astro and Airflow features, in order to better advise the technologies on impactful improvements they can make.
• Collaborate to build reusable assets, automation tools, and documented best practices.
• Interact with Domain and Engineering teams to channel product feedback and requirements discussions.
• Work with technology team members to ensure that are realizing value in their Airflow and Astronomer journeys

Skills Required:

• Experience with Apache Airflow in production environments.
• Experience in designing and implementing ETL, Data Warehousing, and ML/AI use cases.
• Proficiency in Python.
• Knowledge of Azure cloud-native data architecture.
• Demonstrated technical leadership on team projects.
• Strong oral and written communication skills.
• Willingness to learn new technologies and build reference implementations.
• Experience in migrating workflows from legacy schedulers (Tidal) to Apache Airflow.
• Experience in integrating with Azure Data Factory pipelines.
• Snowflake and Databricks experience.
• Experience working with containers.
• SQL experience.
• Kubernetes experience, either on-premise or in the cloud.

• Enterprise data experience in regulated environments.