Remote | Data Engineer (AI Coding Agents) — Up to $75/hour

24-MAG is offering a specialized part-time consulting opportunity for experienced data engineers. The role focuses on evaluating frontier coding models through realistic data engineering tasks, utilizing AI coding agents to complete assignments and assess data infrastructure.

Responsibilities:

• Complete and evaluate complex data engineering tasks using frontier AI coding agents
• Review implementations involving ETL and ELT pipelines, data warehouses, analytics platforms, and distributed systems
• Assess technical correctness, maintainability, scalability, and production readiness
• Apply professional engineering judgment to realistic data infrastructure scenarios
• Use AI coding agents within practical data engineering workflows
• Evaluate how effectively models interpret requirements and implement technical solutions
• Identify bugs, edge cases, incomplete implementations, and failure modes
• Assess where generated solutions require correction or additional engineering work
• Review model-generated data pipelines and supporting infrastructure
• Evaluate ingestion, transformation, storage, orchestration, and data-processing logic
• Identify scalability, reliability, performance, and data-quality concerns
• Assess implementations intended for large-scale or distributed environments
• Compare solutions produced by multiple frontier coding models
• Assess differences in architecture, implementation quality, technical reasoning, and reliability
• Identify recurring strengths and weaknesses across model outputs
• Provide clear written assessments explaining relevant engineering trade-offs

Requirements:

• At least 2 years of professional data engineering experience
• Hands-on experience building ETL pipelines, data warehouses, analytics platforms, or distributed data systems
• Experience operating or supporting large-scale data platforms
• Regular use of AI coding agents within engineering workflows
• Strong ability to evaluate model-generated data infrastructure and pipeline implementations
• Experience debugging complex data-processing or infrastructure issues
• Strong technical judgment, written communication, and attention to detail
• Ability to work effectively within short, intensive project sprints
• A degree in computer science, data engineering, software engineering, information systems, or a related technical discipline may be helpful
• Advanced technical training in distributed systems, databases, cloud infrastructure, or data platforms may strengthen an application
• Equivalent professional experience building production data systems may also be considered
• Practical engineering depth is particularly valuable for this engagement
• Experience with large-scale distributed data platforms
• Familiarity with cloud-based data warehouses and analytics systems
• Knowledge of workflow orchestration, data transformation, and pipeline monitoring
• Experience with Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable AI coding tools
• Background in data quality, performance optimisation, or infrastructure reliability
• Experience reviewing code or technical implementations created by other engineers
• Previous exposure to AI evaluation, benchmark development, or structured technical review