Use when for data lake engineering implementation.
Scanned 9/10/2026
Install to Claude Code
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---
name: data-lake-engineering-implementation
description: "Use when for data lake engineering implementation."
version: 1.0.0
author: Hermes Agent
license: MIT
platforms: [linux, macos, windows]
metadata:
hermes:
tags: [database, data-lake, storage]
related_skills: [general]
---
## Overview
Build data lake systems.
## When to Use
- "Data Lake Engineering Implementation design"
- "Best practices"
- "Optimization"
- "Troubleshooting"
## Key Approaches
1. Requirements
2. Tools
3. Implementation
4. Testing
5. Docs
6. Monitoring
## Common Pitfalls
1. Ignoring constraints
2. Skipping standards
3. Poor alignment
4. Inadequate testing
5. No docs
6. Over-engineering
7. No rollback
8. No monitoring
9. No scaling
10. No validation
## Verification Checklist
- [ ] Requirements verified
- [ ] Standards applied
- [ ] Design reviewed
- [ ] Tests defined
- [ ] Docs complete
- [ ] Monitoring set
- [ ] Rollback planned
- [ ] Security checked
- [ ] Deploy verified
- [ ] Stakeholder approved
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