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

24-Mag•New York, NY

20h•$0 - $75•Remote

About The Position

We are sharing a specialised part-time consulting opportunity for experienced data engineers with hands-on expertise in ETL pipelines, data warehouses, analytics platforms, distributed data systems, and AI-assisted coding workflows. This sprint-based role supports an advanced AI research initiative focused on evaluating frontier coding models through realistic data engineering tasks. Selected professionals will use AI coding agents to complete technical assignments, review model-generated data infrastructure, identify scalability and reliability issues, and compare model performance across practical engineering scenarios.

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

Nice To Haves

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

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

Benefits

Independent contractor role
Fully remote with flexible scheduling
Sprint-based project with task windows typically spanning approximately 12–24 hours
Compensation is $400 per accepted task
Typical tasks require approximately 2–3 hours after ramp-up
Compensation is tied to successfully accepted work
Competitive compensation equivalent to up to approximately $75 per hour depending on accepted work and task duration
Weekly payments via Stripe or Wise
Work may include pipeline implementation review, AI coding-agent evaluation, debugging, scalability analysis, and model comparison
Projects may be extended, shortened, or adjusted depending on scope and performance
Work will not involve access to confidential or proprietary information from any employer, client, or institution