Airflow Data Engineer Jobs

US data engineer openings whose parsed job description names Apache Airflow as the orchestrator. About 700 active listings; Airflow remains the dominant DAG orchestrator in the catalog despite Dagster's growth (about 130 listings) and Prefect's smaller footprint. Managed Airflow flavors (MWAA on AWS, Composer on GCP, Astronomer) account for most of the modern listings.

Airflow Data Engineer Jobs

US data engineer listings that name Apache Airflow in the posting, scored against your profile with salary and layoff signals.

Frequently asked questions

How many Airflow data engineer jobs are listed at once?

Around 700 active listings name Airflow in the parsed JD. Airflow is the modal orchestrator in the catalog, ahead of Dagster (about 130) and Prefect (smaller). The Airflow share has held up better than commentators predicted in 2022-2023 because the managed offerings (MWAA, Composer, Astronomer) made the operations burden tractable for non-platform teams.

Do these Airflow data engineer roles want Airflow 2.x or 3.x?

Mostly 2.x today (2026), with a growing slice expecting 3.x for greenfield work. The 2.x to 3.x migration started in late 2025 and is in progress at many companies; postings often list 'Airflow 2.x required, 3.x experience preferred'. Concepts that carry: TaskGroups, Datasets and data-aware scheduling, deferrable operators, Connection plus Variable management.

What Airflow-specific concepts come up in these data engineer interviews?

Five recur. Idempotency in operators (the same DAG run replayed must produce the same result). Backfill semantics (catchup=True vs False, max_active_runs). Cross-DAG dependencies (Datasets in 2.4+, the old ExternalTaskSensor anti-pattern). Sensor backoff and the deferrable-operator migration. Custom operator design (when to write one vs use a PythonOperator).

What's the typical Airflow stack for the data engineer jobs in this catalog?

Three common shapes. MWAA on AWS: Airflow plus S3 plus Redshift or Snowflake. Composer on GCP: Airflow plus BigQuery plus dbt. Astronomer (managed multi-cloud): Airflow plus Snowflake plus dbt plus Slack notifications. Self-hosted Airflow still appears at companies with strict data-residency requirements; the operations burden keeps it shrinking.

How does Airflow compare to Dagster in the catalog?

Airflow shows up in about 700 listings, Dagster in about 130. The gap has narrowed each year since 2022. Dagster's asset-based model and stronger type system appeal to data-team leads building greenfield platforms; Airflow's incumbent advantage and tooling ecosystem (operators, providers, MWAA, Composer) keep it dominant in the catalog. Companies running both during a migration appear in roughly 30 listings.

Are most Airflow data engineer roles remote?

Slightly above catalog average. Airflow-tagged roles correlate with platform-team and data-platform roles, which trend more remote-friendly than embedded-analytics DE roles. The explicit remote-flagged share runs around 5 to 6 percent, slightly above the 4 percent catalog average. Combine the Airflow filter with Remote on the left rail to see the explicit set.

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