Data Engineer - Fully Remote | Upto $80/hr

mercor; San Francisco (CA); Hybrid; CAD 94,000 - 127,000; Part time

Job summary

Mercor is seeking a Data Engineer (Coding Agent Experience) for remote work under a contract arrangement. The role focuses on using frontier AI coding agents to perform and assess complex data engineering tasks, including ETL pipelines and analytics platforms.

The candidate will review model-generated data infrastructure implementations, identify issues, and apply engineering judgment to real-world scenarios. Prior experience with AI coding agents and distributed data systems is required.

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 experience

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.

Originally posted on Himalayas