Remote | Data Infrastructure Evaluation Engineer — Up to $90/hour
24-Mag•New York, NY
•$90 - $90•Remote
About The Position
We are sharing a specialised remote consulting opportunity for experienced data engineers with strong coding agent experience, practical data infrastructure judgment, and the ability to evaluate complex data engineering implementations across realistic technical scenarios. This role supports current and upcoming remote consulting opportunities focused on data engineering evaluation, coding-agent-assisted technical workflows, pipeline assessment, data platform review, and distributed data system analysis. Selected professionals may use tools such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable coding agents to complete, review, and evaluate data engineering tasks involving ETL pipelines, data warehouses, analytics platforms, distributed systems, and large-scale data infrastructure.
Requirements
- 2+ years of professional data engineering experience
- Hands-on experience building ETL pipelines, data warehouses, analytics platforms, distributed data systems, or large-scale data infrastructure
- Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable tools
- Ability to evaluate generated data infrastructure and pipeline implementations for correctness, scalability, and reliability
- Strong understanding of data modelling, data quality, orchestration, distributed processing, warehouse design, and pipeline maintainability
- Clear written communication skills and comfort documenting technical reasoning in a remote, project-based environment
Nice To Haves
- Experience with Python, SQL, Spark, Airflow, dbt, Kafka, Flink, Snowflake, BigQuery, Redshift, Databricks, or comparable data tools
- Familiarity with cloud data platforms, data lakehouse architecture, orchestration systems, batch processing, streaming pipelines, or data quality frameworks
- Experience with CI/CD workflows, Docker, Kubernetes, Terraform, observability tooling, or infrastructure automation in data environments
- Background in technical code review, data architecture review, pipeline performance evaluation, or large-scale analytics systems
- Strong comfort working in sprint-based project environments with focused technical assessment windows
- Experience supporting large-scale data platforms is strongly preferred
Responsibilities
- Use modern coding agents to complete and evaluate complex data engineering tasks
- Review generated implementations involving ETL pipelines, data warehouses, analytics platforms, and distributed data systems
- Assess technical outputs for correctness, scalability, maintainability, reliability, and production-readiness
- Apply professional data engineering judgment to realistic infrastructure and pipeline scenarios
- Evaluate pipeline architecture, data transformation logic, ingestion workflows, orchestration patterns, and data quality checks
- Review data warehouse and analytics platform implementations for performance, accuracy, structure, and maintainability
- Identify bugs, edge cases, scalability issues, failure modes, and weak assumptions in data engineering outputs
- Provide structured feedback on data flow, system design, reliability, and implementation quality
- Compare outputs from multiple coding agents and assess their strengths, weaknesses, accuracy, and practical usefulness
- Identify where generated solutions succeed, where they fail, and where additional engineering judgment is required
- Evaluate whether generated data infrastructure reflects real-world data engineering standards
- Document technical review findings clearly for project teams and quality evaluation workflows
- Produce clear, structured evaluations of data engineering tasks and generated outputs
- Explain reasoning around pipeline design, data modelling, warehouse architecture, distributed systems, scalability, and failure handling
- Support technical assessment workflows by documenting accepted work, improvement areas, and practical engineering conclusions
- Help ensure outputs reflect production-scale data engineering expectations
Benefits
- Remote consulting work aligned with data engineering, coding agent, and technical evaluation expertise
- Opportunity to evaluate realistic data engineering workflows involving ETL pipelines, data warehouses, analytics platforms, and distributed data systems
- Suitable for engineers who enjoy technical assessment, tool-assisted coding workflows, pipeline review, and practical data infrastructure problem-solving
- Sprint-based project work that can align with focused availability and remote schedules
- Independent contractor engagement
- Fully remote and flexible scheduling
- Sprint-based, project-based availability
- Some project work may run in focused 12–24 hour sprint windows depending on project requirements
- Compensation may reach up to $90/hour, depending on project scope, experience, and accepted work structure
- Some projects may use accepted-task compensation depending on the specific workflow
- Payments are made weekly via Stripe or Wise based on services rendered
- Projects may be extended, shortened, adjusted, or concluded based on project needs and performance
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What This Job Offers
Career Level
Senior
Education Level
Associate degree
