Analytics Engineer

Mercor•San Francisco, CA

23h•$250,000 - $400,000•Onsite

About The Position

Mercor is hiring an Analytics Engineer to build data infrastructure, analytics, and automations that support decision-making and operations across the company. This is a high-ownership role involving direct work with business leaders to identify problems, define roadmaps, and deliver end-to-end solutions. The role calls for proactively finding bottlenecks and opportunities, applying strong technical ability and business judgment, and using AI tools to increase productivity in a high-intensity environment. The position is based in Mercor’s San Francisco office five days per week. The company describes its pace as exceptionally fast and says teams commonly work 9 AM–9 PM.

Requirements

8+ years of experience in Analytics Engineering, Data Engineering, Data Science, or a related technical role.
Expert SQL skills and strong data modeling, Python, dbt, cloud data warehouse, and BI tool skills.
Ability to independently identify problems, define roadmaps, and deliver high-impact projects with minimal direction.
Strong business judgment and communication skills, including the ability to work with senior stakeholders and translate ambiguity into actionable solutions.
Ability to quickly learn unfamiliar domains and technologies and use AI tools to increase productivity.
Track record of delivering high-quality work at exceptional speed, taking ownership beyond formal responsibilities, and thriving in demanding, fast-moving environments.
Willingness to work in the San Francisco office five days per week and to meet the role’s high level of commitment and execution.

Responsibilities

Partner with stakeholders, proactively identify high-impact problems, prioritize work, and execute solutions.
Develop reliable data pipelines, models, and metrics using SQL, dbt, and Snowflake.
Translate ambiguous business problems into production-ready data models, dashboards, and analytical tools.
Identify operational bottlenecks and build automations to eliminate manual work and improve efficiency.
Use AI coding agents and emerging tools to accelerate development and improve analytics engineering workflows.