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/engineering-data-pipelines

Data 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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code-abyss
24530 skills

Claude Code

$ npx -y skills add telagod/code-abyss --skill engineering-data-pipelines --agent claude-code

SKILL.md

engineering-data-pipelines.SKILL.md
name: engineering-data-pipelines
description: Data 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.
user-invocable: false

数据工程域 · Data Engineering

> **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](references/details.md)

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Questions about engineering-data-pipelines.

Which coding agents can use engineering-data-pipelines?
engineering-data-pipelines installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.