Analytics Engineer Intern: Build Scalable Data Pipelines

CryptoproNetwork; San Francisco (CA); Hybrid; USD 57,000 - 81,000; Full time

Job summary

Coinbase is seeking an Analytics Engineer Intern to join the Analytics Engineering team in San Francisco. The 12-week summer internship focuses on building scalable data pipelines, modeling complex data, and delivering self-serve analytics for product and business teams.

You'll work with SQL, Python, and generative AI-assisted workflows, receive mentorship from senior engineers, and gain hands-on experience deploying production data systems at scale.

Qualifications

• Pursuing a degree in computer science, data science, statistics, economics, or a related quantitative field, or equivalent experience.
• Proficient in SQL with the ability to write complex queries, joins, window functions, and aggregations.
• Familiar with Python or another programming language.
• Ability to communicate technical concepts clearly to diverse audiences.
• Uses generative AI responsibly to improve workflow efficiency and quality.

Responsibilities

• Build and maintain dimensional data models transforming raw data into clean datasets for analysts and product teams.
• Develop data pipelines using SQL with a focus on data quality and production readiness.
• Collaborate with stakeholders to deliver well-structured datasets or dashboards for self-serve analytics.
• Leverage generative AI tools to streamline data development, modeling, and documentation.
• Investigate data quality issues and implement tests and monitors.

Skills

SQL

Python

Communication

Generative AI usage

Education

Quantitative degree or equivalent experience

Tools

Generative AI tools

Job description

Coinbase is seeking an Analytics Engineer Intern to join the Analytics Engineering team in San Francisco. The 12-week summer internship focuses on building scalable data pipelines, modeling complex data, and delivering self-serve analytics for product and business teams.

You'll work with SQL, Python, and generative AI-assisted workflows, receive mentorship from senior engineers, and gain hands-on experience deploying production data systems at scale.