{"id":3290577,"url":"https://alion.io/job/mercor-data-engineering-specialist-fully-remote-upto-80hr","title":"Data Engineering Specialist - Fully Remote | Upto $80/hr","company":{"id":4960,"name":"Mercor","domain":"mercor.com","url":"https://alion.io/company/mercor","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":88,"open_postings":15,"ghost_share":0,"stale_share":0.267,"repost_share":0,"time_to_fill_p50_days":76,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"ETL/ELT","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Windsurf","optional":false}],"status":"live","first_seen_at":"2026-10-09T17:22:07Z","employer_posted_date":null,"last_verified_at":"2026-10-09T17:22:07Z","board_verified":false,"closed_at":null,"days_open":20,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":20},"description":"About the jobMercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.\nPosition: Data Engineer (Coding Agent Experience)\nType:Contract\nCompensation:$80/hour\nLocation:Remote\nRole Responsibilities\nUse frontier AI coding agents to complete and evaluate complex data engineering tasks.\n\nReview model-generated implementations involving ETL pipelines, data warehouses, analytics platforms, and distributed data systems.\n\nIdentify bugs, edge cases, scalability issues, and failure modes in model outputs.\n\nCompare outputs from multiple frontier models and assess their strengths and weaknesses.\n\nApply professional engineering judgment to realistic data engineering scenarios.\n\nQualifications\nMust-Have\n\n2+ years of professional data engineering experience.\n\nExperience building ETL pipelines, data warehouses, analytics platforms, or distributed data systems.\n\nRegular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.\n\nAbility to evaluate model-generated data infrastructure and pipeline implementations.\n\nPreferredExperience operating large-scale data platforms.\nCompensation & Legal\n$400 per accepted task.\n\nCompensation is tied to accepted work.\n\nApplication Process (Takes 20–30 mins to complete)\nUpload resume\n\nAI interview based on your resume\n\nSubmit form\n\nResources & Support\nFor details about the interview process and platform information, please check: \n\nFor any help or support, reach out to: \n\nPS: Our team reviews applications daily. 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