'airflow' 검색 결과

Think and work like an expert Data Engineer. Use when a task calls for Data Engineer judgment. Reasons from idempotent ELT, medallion bronze/silver/gold, Kimball grain and SCD2, CDC/Debezium and watermark incremental loads, dbt/GX quality gates, Airflow/Dagster orchestration, Iceberg/Delta lakehouse MERGE, data contracts and freshness SLIs while treating silent join drops, duplicate amplification, schema drift, and green-DAG-wrong-numbers as first-class failure modes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Think and work like an expert Biosystems & Agricultural Process Engineer. Use when a task calls for Biosystems & Agricultural Process Engineer judgment. Reasons from coupled heat and mass transfer, moisture sorption (EMC/ERH on D245.7 isotherms), respiration, and closed unit-operation balances through ASABE standards (S352.2 oven moisture, S448 Page thin-layer kinetics, D272.3 airflow resistance), psychrometric aeration analysis, and SuperPro/Aspen bioprocess simulation while treating wet- vs dry-basis mixing, aeration that wets cool grain, case-hardened wet cores, and grain engulfment and dust explosion as first-class failure modes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Data pipeline specialist for ETL design, data quality, CDC patterns, and batch/stream processingUse when "data pipeline, etl, cdc, data quality, batch processing, stream processing, data transformation, data warehouse, data lake, data validation, data-engineering, etl, cdc, batch, streaming, data-quality, dbt, airflow, dagster, data-pipeline, ml-memory" mentioned.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when adding or changing a scheduled data or ML pipeline — Dagster assets, Prefect flows, Airflow DAGs or a cron'd entrypoint — idempotent partitioned stages, retries, backfills, quality gates, and testing the pipeline without the scheduler

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designing ETL/ELT pipelines, visualizing data flows, selecting batch/streaming approaches, and architecting Kafka/Airflow/dbt systems. Use when building data pipelines or managing data quality.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Instructions for managing CI pipelines, GitHub Actions workflows, Airflow DAGs, and automation scripts in the insurance analytics project.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dbt Core/Cloud data transformations, testing, documentation, and CI/CD. Activate on: dbt, data transformation, analytics engineering, ref, source, staging model, mart, dbt test. NOT for: orchestration/scheduling (use airflow-dag-orchestrator), data warehouse tuning (use data-warehouse-optimizer).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Construa pipelines de dados escaláveis, data warehouses modernos e arquiteturas de streaming em tempo real. Implementa Apache Spark, dbt, Airflow e plataformas de dados nativas em nuvem.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Apache Airflow, dbt, Prefect, Dagster, and modern data orchestration for production data pipelines

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dbt Core/Cloud data transformations, testing, documentation, and CI/CD. Activate on: dbt, data transformation, analytics engineering, ref, source, staging model, mart, dbt test. NOT for: orchestration/scheduling (use airflow-dag-orchestrator), data warehouse tuning (use data-warehouse-optimizer).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.