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Specialised Part-Time Consulting Opportunity for Experienced Data EngineersWe 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.Key ResponsibilitiesComplete and evaluate complex data engineering tasks using frontier AI coding agentsReview implementations involving ETL and ELT pipelines, data warehouses, analytics platforms, and distributed systemsAssess technical correctness, maintainability, scalability, and production readinessApply professional engineering judgment to realistic data infrastructure scenariosAI Coding Agent TestingUse AI coding agents within practical data engineering workflowsEvaluate how effectively models interpret requirements and implement technical solutionsIdentify bugs, edge cases, incomplete implementations, and failure modesAssess where generated solutions require correction or additional engineering workPipeline & Infrastructure ReviewReview model-generated data pipelines and supporting infrastructureEvaluate ingestion, transformation, storage, orchestration, and data-processing logicIdentify scalability, reliability, performance, and data-quality concernsAssess implementations intended for large-scale or distributed environmentsModel Comparison & Technical FeedbackCompare solutions produced by multiple frontier coding modelsAssess differences in architecture, implementation quality, technical reasoning, and reliabilityIdentify recurring strengths and weaknesses across model outputsProvide clear written assessments explaining relevant engineering trade-offsIdeal ProfileStrong candidates may have:At least 2 years of professional data engineering experienceHands-on experience building ETL pipelines, data warehouses, analytics platforms, or distributed data systemsExperience operating or supporting large-scale data platformsRegular use of AI coding agents within engineering workflowsStrong ability to evaluate model-generated data infrastructure and pipeline implementationsExperience debugging complex data-processing or infrastructure issuesStrong technical judgment, written communication, and attention to detailAbility to work effectively within short, intensive project sprintsEducational BackgroundA degree in computer science, data engineering, software engineering, information systems, or a related technical discipline may be helpfulAdvanced technical training in distributed systems, databases, cloud infrastructure, or data platforms may strengthen an applicationEquivalent professional experience building production data systems may also be consideredPractical engineering depth is particularly valuable for this engagementNice to HaveExperience with large-scale distributed data platformsFamiliarity with cloud-based data warehouses and analytics systemsKnowledge of workflow orchestration, data transformation, and pipeline monitoringExperience with Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable AI coding toolsBackground in data quality, performance optimisation, or infrastructure reliabilityExperience reviewing code or technical implementations created by other engineersPrevious exposure to AI evaluation, benchmark development, or structured technical reviewWhy This OpportunityWork directly with frontier AI coding agents on realistic data engineering problemsApply professional data engineering expertise to advanced AI evaluationReview complex pipelines, data infrastructure, and distributed-system implementationsIdentify subtle technical and scalability failures in model-generated solutionsCompare multiple coding systems across practical engineering workflowsParticipate in intensive technical sprints with task-based compensationContract DetailsIndependent contractor roleFully remote with flexible schedulingSprint-based project with task windows typically spanning approximately 12–24 hoursCompensation is $400 per accepted taskTypical tasks require approximately 2–3 hours after ramp-upCompensation is tied to successfully accepted workCompetitive compensation equivalent to up to approximately $75 per hour depending on accepted work and task durationWeekly payments via Stripe or WiseWork will not involve access to confidential or proprietary information from any employer, client, or institutionAbout the PlatformThis opportunity is available through 24-MAG LLC. 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