数据工程域 · Data Engineering
SkillDatabases & dataData engineering knowledge reference covering Airflow, Dagster, Kafka Streams, Flink, dbt, and data quality patterns. Use when building data pipelines, ETL workflows, stream processing, or data quality checks.
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What this skill tells your AI
The instructions your AI receives, as published by telagod/code-abyss in skills/engineering-data-pipelines/SKILL.md and read by ahel’s review.
判断先于执行：决定「是否做 / 选什么 / 如何取舍」（栈、方案、架构、权衡）前，先读领域判断内核
skills/_kernel/backend/SKILL.md——它管 judgment，本秘典管 execution；冲突时以内核判断为准。
编排：Airflow(调度) | Dagster(资产) | Prefect(现代流)
流处理：Kafka Streams(嵌入式) | Flink(集群) | Spark Streaming
质量：Great Expectations | dbt tests | Soda Core
编排检查项
幂等(UPSERT/分区覆盖) | 增量(WHERE updated_at > last_run) | 事件驱动触发 | 跨 DAG 依赖 | 数据血缘(ref()/Asset deps)
流处理检查项
时间语义选择 | Watermark 乱序容忍 | 状态 TTL 防膨胀 | Checkpoint 间隔 | 端到端 Exactly-Once | 背压监控
质量检查项
分层验证(源→转换→目标) | 完整性+准确性+一致性 | 及时性阈值 | 加权评分 | 告警(Slack/PagerDuty)
工具对比、API 用法、质量维度详见 references/details.md
Signals
- GitHub stars
- 239
- Forks
- 32
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
engineering-data-pipelines- Source
- github.com/telagod/code-abyss