Airflow Production Reliability Review

Review this Apache Airflow DAG as if it operates a tier-1 production pipeline. Analyze the code; do not execute it. Airflow version and executor: [version, Celery/Kubernetes/etc.] SLA and schedule: [details] Expected data volume and task duration: [details] Backfill/catchup requirements: [details] Known incidents or pain points: [details] DAG code: [Paste DAG and custom operator code] Evaluate: 1. Idempotency and atomicity of every task write 2. Logical-date/data-interval correctness and avoidance of wall-clock coupling 3. Retries, exponential backoff, timeouts, and non-retryable failures 4. Catchup, backfill, max_active_runs, pools, and concurrency behavior 5. Sensor mode, deferrable operators, dynamic mapping, and scheduler load 6. XCom size, secret handling, templating, and serialization risks 7. Partial-failure recovery and safe manual reruns 8. Data-quality gates, lineage, metrics, and alert routing 9. Separation of orchestration from business logic 10. Unit, DAG-parse, integration, and idempotency tests Return findings as Blocker/High/Medium/Low with line references, corrected snippets for the top issues, and a go/no-go recommendation.