[Hiring] Data Warehouse Engineer @Mercor

Role Description

• 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

• Must-Have 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.

Requirements

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

Application Process

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

Resources & Support

• 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: [email protected]
• Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.