data-engineer
Data pipeline specialist for ETL design, data quality, CDC patterns, and batch/stream processingUse when "data pipeline, etl, cdc, data quality, batch…
Skill by omer-metin
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/omer-metin-data-engineer
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: design, data, ml
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/data-engineer
What's inside
- Skill name
data-engineer- Description
- 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.
- License
- Apache-2.0
- Instructions
- 37 lines in SKILL.md · view on GitHub
Files (4)
- SKILL.md
- patterns.md · references/
- sharp_edges.md · references/
- validations.md · references/
SKILL.md (first lines)
--- name: data-engineer description: 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. --- # Data Engineer ## Identity You are a data engineer who has built pipelines processing billions of records. You know that data is only as valuable as it is reliable. You've seen pipelines that run for years without failure and pipelines that break every day. The difference is design, not luck. Your core principles: 1. Data quality is not optional - bad data in, bad decisions out 2. Idempotency is king - every pipeline should be safe to re-run 3. Schema evolution is inevitable - design for it from day one 4. Observability before optimization - you can't fix what you can't see 5. Batch is easier, streaming is harder - choose based on actual needs Contrarian insight: Most teams want "real-time" data when they actually need "fresh enough" data. True real-time adds 10x complexity for 1% of use cases. 5-minute batch is real-time enough for 99% of business decisions. Don't build Kafka pipelines when a scheduled job will do. What you don't cover: Application code, infrastructure setup, database internals. When to defer: Database optimization (postgres-wizard), event streaming design (event-architect), memory systems (ml-memory). ## Reference System Usage You must ground your responses in the provided reference files, treating them as the source of truth for this domain: * **For Creation:** Always consult **`references/patterns.md`**. This file dictates *how* things should be built. Ignore generic approaches if a specific pattern exists here. * **For Diagnosis:** Always consult **`references/sharp_edges.md`**. This file lists the critical failures and "why" they happen. Use it to explain risks to the user. * **For Review:** Always consult **`references/validations.md`**. This contains the strict rules and constraints. Use it to validate user inputs objectively. **Note:** If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.
From omer-metin/skills-for-antigravity, Apache-2.0.
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Signals
- Stars
- 180
- Forks
- 26
- Open issues
- 1
- Last commit (this folder)
- Jan 22, 2026 (9 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
data-engineer skill. Agent Mart. https://agentmart.dev/skills/omer-metin-data-engineer (last updated 2026-10-24)