Data Engineer - Fully Remote | Upto $80/hr

Obsidian; San Francisco (CA); Remote; USD 454,608 - 647,472; Part time

Job summary

Obsidian is seeking contributors for a project with a leading AI research lab focused on evaluating frontier AI coding models. You'll complete and assess complex data engineering tasks using AI coding agents.

The role requires at least 2 years of experience in data engineering and familiarity with ETL pipelines and data systems. Compensation is project-based, with $400 per accepted task, typically taking 2–3 hours to complete.

Qualifications

• 2+ years of professional data engineering experience.
• Experience with ETL pipelines and data warehouses.
• Familiarity with AI coding agents.

Responsibilities

• Use AI coding agents for complex data engineering tasks.
• Review model-generated implementations.
• Identify bugs and scalability issues.

Skills

Data engineering experience

Building ETL pipelines

Using AI coding agents

Evaluating model-generated implementations

Tools

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Job description

About the Role

• Mercor is partnering with a leading AI research lab to support a Frontier Code Agents project.
• Contributors help evaluate and improve frontier AI coding models through structured technical assessments.
• The work focuses on realistic data engineering workflows and model evaluation.
• Spots are limited and filling quickly on a first come, first serve basis.

What You'll Do

• 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.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic data engineering scenarios.

Time Commitment

Sprint based project that runs in 12-24 hour stretches based on client requirement.

Compensation

• $400 per accepted task.
• Typical tasks take approximately 2–3 hours after ramp-up.
• Compensation is tied to accepted work.

Who Should Apply

• 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.
• Experience operating large-scale data platforms is preferred.