Role overview

This is a 12-week summer internship with Coinbase’s Analytics Engineering team, part of the Platform division. You will work on building and maintaining the data infrastructure that supports decision-making across the organization, gaining hands-on experience with production-scale data systems while receiving mentorship from senior analytics engineers.

Key responsibilities

Build and maintain dimensional data models that transform raw data into clean, reliable datasets for use by analysts, data scientists, and product teams throughout the company.
Develop data pipelines using SQL while ensuring data quality, freshness, and documentation meet production standards.
Work with cross-functional teams to understand their data requirements and deliver well-structured datasets or dashboards that enable self-service analytics capabilities.
Use generative AI tools to improve efficiency in data development, modeling, and documentation workflows.
Identify and resolve data quality issues by implementing tests and monitoring systems that detect problems before they impact downstream users.

Requirements

Currently enrolled in a degree program in computer science, data science, statistics, economics, or a related quantitative field, or equivalent professional experience.
Demonstrated proficiency in SQL through coursework, projects, or prior internship work, with capability to write complex queries involving joins, window functions, and aggregations.
Familiarity with at least one programming language, with Python being preferred.
Ability to communicate technical concepts effectively to both technical and non-technical audiences through project presentations, dashboards, documentation, or team collaboration.
Responsible use of generative AI tools with appropriate human oversight to ensure business-ready outputs and measurable improvements in workflow efficiency, cost, and quality.

What makes this role worth considering

You’ll gain exposure to how data powers decision-making at a publicly traded cryptocurrency-native company while working on infrastructure that scales across the entire organization. The role offers mentorship from experienced analytics engineers and practical experience building production systems at scale, all in a hybrid work environment in New York.