Data Engineer - Fully Remote

About the job

Mercor 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.

Location: Remote

• Build long-horizon pipeline tasks with deterministic rubrics to grade agent performance against verifiable ground truth.
• Develop ETL/ELT pipelines and dbt models to produce specified output tables with incremental logic and defined watermark behavior.
• Create Airflow/Dagster DAGs that pass test suites and data quality tests with known pass/fail cases.
• Design warehouse schemas matching defined contracts and performance targets tied to measured query-time budgets.
• Work independently in long focus sessions to create challenging scenarios for agent evaluation.
• Ensure tasks have checkable answers without open-ended essays or subjective judgment calls.

Qualifications

• BS or MS in CS or related field.
• 3+ years in data engineering or analytics engineering.
• Expertise in dbt model development, pipeline orchestration (Airflow, Dagster, Prefect), warehouse design (Snowflake, BigQuery, Redshift, Databricks), and data quality and testing.
• Comfortable with data engineering artifacts: dbt models, DAGs, schema docs, data contracts, and test suites.
• Clear written communication skills to articulate reasoning and encode it into deterministic rubrics.

• Hourly contractor
• Strong contributors are promoted based on task quality and throughput.

• Upload resume
• AI interview based on your resume
• Submit form

• For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
• For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.