Data Engineering Specialist - Fully Remote | Upto $80/hr

mercor

San Francisco (CA)

Hybrid

GBP 71,000 - 96,000

Full time

4 days ago
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Job summary

Mercor is seeking a Data Engineer (Coding Agent Experience) for remote, contract work. The role centers on applying frontier AI coding agents to real-world data infrastructure challenges.

You will review model-generated ETL pipelines, data warehouses, analytics platforms and distributed systems, identify issues, and apply engineering judgment to scalable solutions.

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
Data Warehouses
Distributed Systems
AI Agents

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.
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