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Remote Apache Airflow Jobs

Browse vetted remote Airflow positions at companies running production ML pipelines — DAG engineering, workflow orchestration, and MLOps automation roles.

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Remote worldwide
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Airflow Engineer ML Pipeline Engineer Data Workflow Developer MLOps Engineer Data Platform Engineer

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Jobs & Projects

Nebius

Posted 10 hours ago

Senior Data Engineer

senior
Full-time
English
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Motional
Full-time
English
$172K – $229K / year
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Motional
senior
Full-time
English
$149K – $199K / year
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Motional

Posted 14 hours ago

Senior Release Engineer

senior
Full-time
English
$149K – $199K / year
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Eve

Posted 21 hours ago

Senior Data Engineer

senior
Full-time
English
$185K – $210K / year
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Prolific

Posted 1 day ago

Data Engineer

Full-time
English
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A
Full-time
English
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A
Full-time
English
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Astronomer
senior
Full-time
English
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Wayve

Posted 2 days ago

Data Engineer, App SW

Full-time
English
machine learning python sql machine learning spark +1 more
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Role guide

What to expect in remote Airflow jobs

Apache Airflow is the most widely deployed ML pipeline orchestration tool. Remote Airflow jobs involve designing maintainable DAGs, integrating Airflow with cloud data infrastructure, and ensuring ML training pipelines run reliably. Engineers with Airflow experience plus ML system knowledge are in consistent demand.

What you'll work on

  • Build Airflow DAGs that automate ML model retraining on schedule or data trigger
  • Orchestrate multi-step pipelines across Spark, dbt, and ML systems
  • Monitor and alert on pipeline failures in production data workflows
  • Migrate fragile cron jobs to reliable, retryable Airflow workflows

What companies look for

  • Production DAG design — modularity, testing, failure handling
  • Airflow operator, sensor, and hook development experience
  • Knowledge of Airflow deployment on Kubernetes or Astronomer

Frequently asked questions

What Airflow roles are available remotely?

Primarily data engineering and MLOps roles where Airflow is part of the orchestration stack. Pure "Airflow engineer" titles are rarer — most roles combine Airflow with Python, cloud platforms, and data tools like dbt or Spark.

Do remote Airflow jobs require Kubernetes experience?

Increasingly yes. KubernetesExecutor and Astronomer deployments are common at scale. Smaller companies may use CeleryExecutor or LocalExecutor — check individual job listings for infrastructure specifics.

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