Mazelb Dev Environment Template Data Engineering

Data Engineering Skill

Automatically optimizes data pipelines, SQL queries, and data quality.

When This Skill Activates

Claude invokes this skill when you:

1. Show SQL queries or database code
2. Mention slow queries or performance
3. Discuss data pipelines or ETL
4. Ask about data quality
5. Work with database schema

What This Skill Does

1. SQL Query Optimization

Identifies:

• N+1 query problems
• Missing indexes
• Inefficient JOINs
• Unnecessary columns in SELECT
• Lack of query limits

Example Optimization:

-- Before: Sequential scan (45ms)
SELECT * FROM users WHERE email = 'test@example.com';

-- Add index
CREATE INDEX idx_users_email ON users(email);

-- After: Index scan (2ms) - 95% faster

2. Data Pipeline Design

Best Practices:

• Idempotency (safe to rerun)
• Error handling and retries
• Monitoring and alerting
• Data validation
• Incremental processing

3. Data Quality

Checks for:

• Schema validation
• Null handling
• Duplicate detection
• Referential integrity
• Data type consistency

Archetype-Specific Optimizations

For rag-project:

• OpenSearch indexing optimization
• Batch document processing
• Embedding caching strategies
• Vector search performance

For api-service:

• Database query optimization
• SQLAlchemy eager loading
• Connection pooling
• Query result caching

Output Format

Provides:

1. Query Analysis: Performance issues
2. Execution Plan: EXPLAIN output
3. Optimized Query: Improved version
4. Index Recommendations: SQL to create indexes
5. Performance Gains: Expected improvements

Example Usage

User: "This query is slow: SELECT * FROM users JOIN profiles..."
Claude: [Activates data-engineering skill]
- Identifies N+1 problem
- Suggests eager loading
- Recommends indexes
- Provides optimized query

Result: 2000ms → 150ms (13x faster)

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