Data Engineer — Apache Airflow
Make data workflows reliable. Help teams get more from their data.
Work model: Fully Remote
THE OPPORTUNITY
Reliable data workflows are the foundation of great data products. We’re looking for Data Engineers with strong Apache Airflow and Python expertise to help teams build, operate, and optimize dependable data pipelines.
In this role, you’ll combine hands-on technical knowledge with customer-facing engineering. You’ll advise data engineering teams, help them integrate their existing tools and infrastructure, and guide them through platform adoption — from initial configuration to production readiness.
If you enjoy troubleshooting complex technical challenges, sharing your knowledge, and helping others build better data workflows, this opportunity is for you.
WHAT YOU’LL DO
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Support customers with Apache Airflow configuration, DAG development, scheduling, and troubleshooting.
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Advise data engineering teams on designing and operating reliable workflows.
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Help integrate Airflow with existing data ecosystems, including cloud data warehouses, transformation tools, and infrastructure-as-code solutions.
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Support customers during platform onboarding, adoption, and production implementation.
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Investigate complex Airflow-related issues and guide customers toward stable, reliable solutions.
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Help identify root causes of production issues across distributed systems.
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Deliver technical guidance and support customers in getting the most out of the platform.
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Collaborate with internal stakeholders to coordinate project scope, track progress, and align on priorities.
WHAT YOU BRING
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Strong hands-on knowledge of Apache Airflow, including DAG development, scheduling, and operational concepts.
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Professional experience with Python.
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Experience supporting or advising data engineering teams in a customer-facing technical role.
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Ability to troubleshoot distributed systems and production issues.
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Excellent communication skills and a customer-oriented mindset.
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Ability to work independently in a fully remote, distributed environment.
NICE TO HAVE
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Practical knowledge of Kubernetes and containerized environments.
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Experience with managed cloud services.
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Familiarity with modern data stack technologies such as Snowflake and dbt.
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Experience delivering technical workshops, training, or enablement sessions.
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Production experience with Airflow administration.
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Exposure to Infrastructure as Code tools such as Terraform.
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Familiarity with SQL and analytical data workflows.
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Background in technical support, platform engineering, or reliability engineering.
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Experience supporting enterprise customers during onboarding and platform adoption.
WHY THIS ROLE?
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Remote flexibility — collaborate with distributed teams from your preferred location.
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Technical variety — work across workflow orchestration, Python, cloud services, and modern data stacks.
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Engineering meets enablement — combine technical problem-solving with direct customer impact.
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Meaningful challenges — help data engineering teams build more reliable and maintainable workflows.
READY TO MAKE DATA WORK BETTER?
If Apache Airflow, Python, and solving real-world data engineering challenges are your strengths, we’d love to hear from you.
Apply now and help engineering teams build more reliable data workflows.
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