Data Engineer vs Ml Engineer

Data Engineer and Ml Engineer are both Claude Code sub-agents, but they're optimized for different use cases. Data Engineer focuses on Expert data engineer specializing in building scalable data pipelines, ETL/ELT processes, and data infrastructure. Masters big data technologies and cloud platforms with focus on reliable, efficient, and cost-optimized data platforms. Use when building data pipelines or ETL processes., while Ml Engineer is better suited for Expert ML engineer specializing in machine learning model lifecycle, production deployment, and ML system optimization. Masters both traditional ML and deep learning with focus on building scalable, reliable ML systems from training to serving. Use when implementing machine learning models or ML pipelines..

The best choice depends on your specific needs. Use Data Engineer when you need Expert data engineer specializing in building scalable data pipelines, ETL/ELT processes, and data infrastructure. Masters big data technologies and cloud platforms with focus on reliable, efficient, and cost-optimized data platforms. Use when building data pipelines or ETL processes.. Choose Ml Engineer when your work requires Expert ML engineer specializing in machine learning model lifecycle, production deployment, and ML system optimization. Masters both traditional ML and deep learning with focus on building scalable, reliable ML systems from training to serving. Use when implementing machine learning models or ML pipelines..

Yes! You can combine multiple sub-agents by including their prompts in your CLAUDE.md file. Many developers use different agents for different parts of their workflow or project.