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Great Value Hiring

Data Engineer (Coding Agent Experience)

Great Value Hiring

United Kingdom · Sözleşme

Başvuran ilk kişi siz olun

Deneyim
2+ yıl
Maaş
USD 80 – USD 80 / hour
Açılışlar
1
Yayınlandı
1 saat önce
Çalışma modu
Ofiste
Sürdürmek
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İş tanımı

Role Overview

As a Data Engineer working with advanced AI coding agents, you will contribute to the assessment and enhancement of leading-edge AI models tailored for data engineering tasks. Your efforts will focus on authentic data engineering workflows and evaluating model outputs to drive improvements.

Key Responsibilities

  • Utilize frontier AI coding agents to execute and assess complex data engineering assignments.
  • Analyze implementations generated by AI models involving ETL pipelines, data warehouses, analytics platforms, and distributed data infrastructures.
  • Detect and report bugs, edge cases, scalability challenges, and failure scenarios.
  • Contrast the outputs produced by multiple frontier AI models to determine their advantages and limitations.
  • Apply professional engineering expertise to practical data engineering situations.

Project Structure and Time Commitment

This is a sprint-style engagement where project tasks occur in concentrated 12-24 hour intervals, responding to client needs.

Candidate Profile

  • Minimum two years of hands-on professional experience in data engineering.
  • Proven skills in constructing ETL pipelines, managing data warehouses, developing analytics platforms, or working with distributed data systems.
  • Regular interaction with AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable tools.
  • Capability to critically review AI-generated data infrastructure and pipeline implementations.
  • Background in operating extensive data platforms is advantageous.

Compensation

  • A payment of $400 is provided for each accepted task.
  • Most tasks require approximately 2-3 hours after an initial familiarization period.
  • Payment is based solely on completed and approved work.

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