Data Engineer

Mercor • San Francisco, CA

93d

About The Position

Mercor is training models that predict how well someone will perform on a job better than a human can. We use our platform to source, vet, and onboard expert contractors who help train AI models in a wide variety of domains. Our technology is so effective it’s used by all of the top 5 AI labs. We scaled from $1-500M in revenue run rate in the last 17 months, making us the fastest growing company in the world. Our growth is accelerating. We averaged 11% week over week growth in July, 18% WoW growth in August, and 19% WoW growth in September. The team is small and we remain profitable because we can’t hire great people as quickly as revenue is growing.

Requirements

• Proven experience in data engineering, with strong knowledge of SQL, Python, and modern data stack tools (Fivetran, dbt, Snowflake or similar).
• Experience building and maintaining large-scale ETL/ELT pipelines across heterogeneous sources (databases, analytics platforms, SaaS tools).
• Strong understanding of data modeling, schema design, and transformation best practices.
• Familiarity with data governance, monitoring, and quality assurance.
• Comfort working cross-functionally with engineering, product, and operations teams.

Nice To Haves

• Prior experience supporting machine learning workflows or analytics platforms.

Responsibilities

• Building robust pipelines to ingest, transform, and consolidate data from diverse sources (e.g., MongoDB, Airtable, PostHog, production databases).
• Designing dbt models and transformations to standardize and unify many disparate tables into clean, production-ready schemas.
• Implementing scalable, fault-tolerant data workflows with Fivetran, dbt, SQL, and Python.
• Partnering with engineers, data scientists, and business stakeholders to ensure data availability, accuracy, and usability.
• Owning data quality and reliability across the stack, from ingestion through to consumption.
• Continuously improving pipeline performance, monitoring, and scalability.

Benefits

• Impact: Your work powers how the world’s leading AI labs train and test their models.
• Learning: Get early insights into frontier model capabilities months before the market.
• Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.

What This Job Offers

• Career Level: Mid Level