PitchMeAI
Mercor

Data Engineer - AI Trainer

Mercor · New York, NY

  • Hybrid
  • Part-time
  • $125,000 / year
  • New York, NY

Job highlights

  • Build AI agent evaluation pipelines.
  • Develop ETL/ELT pipelines and dbt models.
  • Orchestrate tasks with Airflow or Dagster.
  • Design efficient data warehouse schemas.
  • Work remotely on contract basis.

About the role

Data Engineer AI Trainer at Mercor

Mercor is connecting top creative and technical talent with leading AI research labs. We are headquartered in San Francisco and backed by prominent investors including Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

About the Role

Mercor is seeking a Data Engineering Expert for a contract position. This role involves building long-horizon pipeline tasks with deterministic rubrics to grade agent performance against verifiable ground truth. You will develop ETL/ELT pipelines and dbt models, create Airflow/Dagster DAGs, design warehouse schemas, and work independently to create challenging scenarios for agent evaluation.

Role Responsibilities

  • Build long-horizon pipeline tasks with deterministic rubrics.
  • Develop ETL/ELT pipelines and dbt models with incremental logic.
  • Create Airflow/Dagster DAGs that pass test suites.
  • Design warehouse schemas matching defined contracts and performance targets.
  • Work independently in long focus sessions for agent evaluation.
  • Ensure tasks have checkable answers without subjective judgment.

Qualifications

  • BS or MS in Computer Science 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/testing.
  • Comfortable with data engineering artifacts: dbt models, DAGs, schema docs, data contracts, and test suites.
  • Clear written communication skills to articulate reasoning into deterministic rubrics.

Compensation & Legal

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

Application Process (Takes 20–30 mins to complete)

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

Resources & Support

For details about the interview process and platform information, please visit: https://talent.docs.mercor.com/welcome

For any help or support, reach out to: support@mercor.com

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

Key skills/competency

  • Data Engineering
  • AI Training
  • ETL/ELT Pipelines
  • dbt
  • Airflow
  • Dagster
  • Data Warehousing
  • Data Quality
  • SQL
  • Python

Skills & topics

  • Data Engineer
  • AI Trainer
  • ETL
  • ELT
  • dbt
  • Airflow
  • Dagster
  • Snowflake
  • BigQuery
  • Redshift
  • Databricks
  • Data Warehousing
  • Data Quality
  • Pipeline Orchestration
  • Contract
  • Remote
  • Python
  • SQL
  • AI
  • Machine Learning

How to get hired

  • Tailor your resume: Highlight your 3+ years of data engineering experience and expertise in dbt, Airflow/Dagster, and warehouse design.
  • Ace the AI interview: Be prepared for an AI-driven assessment based on your resume.
  • Demonstrate communication: Showcase clear written communication skills for articulating rubrics.
  • Showcase technical skills: Emphasize experience with data engineering artifacts like dbt models and data contracts.
  • Apply promptly: Applications are reviewed daily; complete all steps to be considered.

Technical preparation

Master dbt model development and SQL.,Practice Airflow/Dagster DAG creation.,Study warehouse design principles.,Build data contracts and test suites.

Behavioral questions

Describe a complex data pipeline you built.,How do you ensure data quality?,How do you work independently on tasks?,Explain your communication style for technical reasoning.

Frequently asked questions

What is the application process for the Data Engineer AI Trainer role at Mercor?
The application process for the Data Engineer AI Trainer position at Mercor involves uploading your resume, completing an AI interview based on your resume, and submitting the form. The entire process typically takes 20-30 minutes. Applications are reviewed daily.
What are the key technical skills required for the Data Engineer AI Trainer role?
Key technical skills for the Data Engineer AI Trainer role include expertise in dbt model development, pipeline orchestration (Airflow, Dagster, Prefect), warehouse design (Snowflake, BigQuery, Redshift, Databricks), and data quality/testing. A strong understanding of data engineering artifacts like DAGs, schema docs, and data contracts is also essential.
Is the Data Engineer AI Trainer position at Mercor remote?
Yes, the Data Engineer AI Trainer position at Mercor is a remote role. This allows for flexibility in where you work, provided you have a stable internet connection and can meet the job responsibilities.
What is the compensation for the Data Engineer AI Trainer role?
The compensation for the Data Engineer AI Trainer role is hourly, ranging from $90 to $125 per hour. Strong performers may see opportunities for growth based on task quality and throughput.
What is Mercor's background and who are their investors?
Mercor connects elite creative and technical talent with leading AI research labs. The company is headquartered in San Francisco and is backed by notable investors including Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Does Mercor require a BS or MS degree for the Data Engineer AI Trainer role?
Yes, a Bachelor of Science (BS) or Master of Science (MS) in Computer Science or a related field is a required qualification for the Data Engineer AI Trainer position at Mercor.
How does Mercor ensure objective evaluation for agent performance in this role?
Mercor emphasizes building long-horizon pipeline tasks with deterministic rubrics to grade agent performance. The goal is to have checkable answers without open-ended essays or subjective judgment calls, ensuring verifiable ground truth.