Analytics Engineer

About Mercor

Mercor’s mission is to organize human intelligence for the AI economy. We build the infrastructure that enables frontier AI labs and enterprises to train, evaluate, and improve AI on real-world professional work. More than five million experts have joined our network, and we pay out over $5 million daily for their knowledge and expertise.

We built our training and evaluation infrastructure alongside the world’s leading AI labs. Now, we’re bringing those capabilities to enterprises across industries, enabling them to train, evaluate, and improve AI using their own expertise and standards. Our APEX benchmarks measure how AI performs on economically valuable work, while our enterprise evaluations and post-training capabilities turn those insights into measurable improvements across real-world workflows.

Our work sits at the intersection of frontier AI, human expertise, and real-world application. We’re solving problems few companies have encountered, with the opportunity to influence what the world’s most advanced AI systems become capable of doing. We’re looking for people who bring different perspectives, take ownership, exercise sound judgment, and hold themselves to an exceptionally high standard. You’ll have the opportunity to do consequential work alongside talented colleagues who challenge one another, collaborate openly, and share a commitment to excellence.

Mercor is profitable and recently raised a $750 million Series D at a $20 billion valuation. We work in person five days a week in San Francisco, New York, and London.

About the Role

We’re looking for an Analytics Engineer to build the data infrastructure, analytics, and automations that power decision-making and operations across Mercor.

This is a high-ownership role where you’ll work directly with business leaders to identify problems, define roadmaps, and deliver solutions end-to-end. Rather than waiting for stakeholder requests, you’ll proactively uncover bottlenecks and opportunities, often before others recognize them.

We’re looking for someone with exceptional technical ability, strong business judgment, and a bias for action. You should be a fast learner who leverages AI tools to dramatically increase your productivity and thrives in a high-intensity environment.

What You’ll Do

Drive your own roadmap: Partner directly with stakeholders, proactively identify high-impact problems, and independently prioritize and execute solutions.
Build scalable data infrastructure: Develop reliable data pipelines, models, and metrics using SQL, dbt, and Snowflake.
Own analytics end-to-end: Translate ambiguous business problems into production-ready data models, dashboards, and analytical tools.
Automate business workflows: Identify operational bottlenecks and build automations that eliminate manual work and improve efficiency.
Leverage AI to multiply output: Use AI coding agents and emerging tools to accelerate development and continuously improve how analytics engineering gets done.

What We’re Looking For

8+ years of experience in Analytics Engineering, Data Engineering, Data Science, or a related technical role.
Strong technical fundamentals: Expert SQL, data modeling, Python, dbt, cloud data warehouses, and BI tools (e.g., Hex, Looker).
Exceptional autonomy: Proven ability to independently identify problems, define roadmaps, and deliver high-impact projects with minimal direction.
Strong business judgment and communication: Able to work directly with senior stakeholders, understand business priorities, and translate ambiguity into actionable solutions.
Rapid learning and AI fluency: Quickly master unfamiliar domains and technologies, and leverage AI tools to dramatically increase productivity.
Proven track record of execution: Consistently deliver high-quality work at exceptional speed, take ownership beyond your formal responsibilities, and thrive in demanding, fast-moving environments.

Work Environment

Mercor operates at an exceptionally fast pace. This role is based in our San Francisco office five days per week, and our teams commonly work 9 AM–9 PM. We’re looking for people who are energized by this level of commitment, autonomy, and execution.