Data Engineer – AI Coding Agents

This is a fully remote position, open to applicants in New York.

📋 Description

• Carry out and assess intricate data engineering projects utilizing cutting-edge AI coding agents

• Examine implementations related to ETL and ELT pipelines, data warehouses, analytics platforms, and distributed systems

• Evaluate the technical soundness, maintainability, scalability, and readiness for production

• Utilize professional engineering judgment in realistic data infrastructure situations

• Incorporate AI coding agents into practical data engineering processes

• Assess the effectiveness of models in interpreting requirements and executing technical solutions

• Detect bugs, edge cases, incomplete implementations, and potential points of failure

• Review data pipelines generated by models and their supporting infrastructure

• Analyze ingestion, transformation, storage, orchestration, and the logic behind data processing

• Identify concerns related to scalability, reliability, performance, and data quality

• Compare solutions generated by various frontier coding models

• Evaluate architecture, implementation quality, technical reasoning, and reliability

• Deliver clear written assessments that outline relevant engineering trade-offs

• Engage in intensive technical sprints that include pipeline reviews, AI coding agent assessments, debugging, scalability evaluations, and model comparisons

⛳️ Requirements

• Minimum of 2 years of professional experience in data engineering

• Practical experience in developing ETL pipelines, data warehouses, analytics platforms, or distributed data systems

• Experience in operating or supporting large-scale data platforms

• Regular engagement with AI coding agents in engineering workflows

• Capability to evaluate model-generated data infrastructure and pipeline implementations

• Experience troubleshooting complex data processing or infrastructure challenges

• Strong technical judgment, written communication skills, and meticulous attention to detail

• Ability to work efficiently within short, focused project sprints

• A degree in computer science, data engineering, software engineering, information systems, or a related technical field can be advantageous, but is not mandatory

• Advanced technical training in distributed systems, databases, cloud infrastructure, or data platforms can enhance an application

• Equivalent professional experience in building production data systems may be accepted

• Familiarity with large-scale distributed data platforms

• Knowledge of cloud-based data warehouses and analytics systems

• Understanding of workflow orchestration, data transformation, and pipeline monitoring

• Experience with tools such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar AI coding technologies

• Background in data quality, performance optimization, or infrastructure reliability

• Experience in reviewing code or technical implementations produced by other engineers

• Prior exposure to AI evaluation, benchmark development, or structured technical reviews

🏝️ Benefits

• Flexible scheduling

• Sprint-based project structure with task durations typically ranging from 12 to 24 hours

• Compensation of $400 for each accepted task

• Earnings potentially reaching approximately $75 per hour based on accepted work and task length

• Weekly payments processed via Stripe or Wise

• Possible project extensions or modifications based on scope and performance