Data Engineer - AI Coding Expert

mercor; United States; Remote; USD 96,000 - 124,000; Full time

Job summary

Mercor is seeking a Data Engineer to work on frontier AI coding agent workflows in a fully remote contract role. You will build and evaluate ETL pipelines, data warehouses, analytics platforms, and distributed data systems, using state-of-the-art AI coding agents to implement and test data solutions.

You will review model-generated code, identify edge cases and scalability issues, and apply engineering judgment to realistic data scenarios.

Qualifications

• 2+ years of professional data engineering experience.
• Experience building ETL pipelines, data warehouses, analytics platforms, or distributed data systems.
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated data infrastructure and pipeline implementations.

Responsibilities

• Use frontier AI coding agents to complete and evaluate complex data engineering tasks.
• Review model-generated implementations involving ETL pipelines, data warehouses, analytics platforms, and distributed data systems.
• Identify bugs, edge cases, scalability issues, and failure modes in model outputs.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic data engineering scenarios.

Skills

Data engineering

ETL pipelines

Distributed data systems

Model evaluation

AI coding agents usage

Tools

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Job description

About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .

Position: Data Engineer (Coding Agent Experience) Type: Contract Compensation: $80/hour Location: Remote

Role Responsibilities

• Use frontier AI coding agents to complete and evaluate complex data engineering tasks.
• Review model-generated implementations involving ETL pipelines , data warehouses , analytics platforms , and distributed data systems .
• Identify bugs, edge cases, scalability issues, and failure modes in model outputs.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic data engineering scenarios.

Qualifications

Must-Have

• 2+ years of professional data engineering experience.
• Experience building ETL pipelines , data warehouses , analytics platforms , or distributed data systems .
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated data infrastructure and pipeline implementations.

Preferred

• Experience operating large-scale data platforms.

Compensation & Legal

• $400 per accepted task .
• Compensation is tied to accepted work.

Resources & Support

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