Senior Data Engineer with Airflow

• Providing hands-on assistance with Airflow configuration, DAG design, scheduling, and troubleshooting
• Acting as a technical advisor for customer data engineering teams using diverse technology stacks
• Helping customers integrate Airflow with their existing data ecosystem (e.g. cloud data warehouses, transformation tools, infrastructure as code)
• Supporting customers during initial platform adoption and production onboarding
• Troubleshooting complex Airflow-related issues and guiding customers toward stable, reliable solutions
• Collaborating with an internal project owner responsible for scope management, status tracking, and meeting facilitation

Key requirements:

• Strong hands-on knowledge of Apache Airflow, including DAG development, scheduling, and operational concepts
• Professional experience with Python
• Experience supporting or working with data engineering platforms in a customer-facing or advisory role
• Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery
• Ability to troubleshoot distributed systems and production issues
• Understanding of Kubernetes and containerized environments
• Experience working with managed cloud services
• Familiarity with at least one modern data stack (e.g. Snowflake, dbt, Terraform)

Nice to have:

• Experience with Airflow administration in production environments
• Exposure to infrastructure as code (Terraform or similar)
• Familiarity with SQL and analytical data workflows
• Previous experience in customer support, reliability engineering, or platform engineering roles
• Experience working with enterprise customers during onboarding or adoption phases
• Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches