Analytics Engineer Intern: Build Scalable Data Pipelines

Unchain Data; San Francisco, Northern (CA, KY); Hybrid; USD 57,000 - 81,000; Full time

Job summary

Coinbase is seeking an Analytics Engineer Intern for a 12-week summer internship in 2027. You’ll join the Analytics Engineering team within Platform to build scalable data infrastructure powering decision-making across the company.

As an intern, you’ll model complex data, develop data pipelines with SQL and Python, gain hands-on experience building production data systems, and receive mentorship from senior engineers during in-person surges.

Qualifications

• Pursuing a degree in computer science, data science, statistics, economics or related quantitative field, or equivalent experience.
• Demonstrated proficiency in SQL with ability to write complex queries (joins, window functions, aggregations).
• Familiarity with Python and ability to code basic data scripts.
• Ability to communicate technical concepts clearly to technical and non-technical audiences.
• Uses generative AI responsibly with human oversight to deliver business-ready outputs.

Responsibilities

• Build and maintain dimensional data models transforming raw data into clean, reliable datasets.
• Develop data pipelines using SQL, ensuring data quality and production-grade documentation.
• Partner with cross-functional stakeholders to deliver well-structured datasets or dashboards.
• Leverage generative AI tools to streamline data development and documentation workflows.
• Investigate and resolve data quality issues with tests and monitors.

Skills

SQL proficiency

Python

Communication

Education

Bachelor's degree in CS/Data Science/Statistics/Economics or related

Job description

Coinbase is seeking an Analytics Engineer Intern for a 12-week summer internship in 2027. You’ll join the Analytics Engineering team within Platform to build scalable data infrastructure powering decision-making across the company.

As an intern, you’ll model complex data, develop data pipelines with SQL and Python, gain hands-on experience building production data systems, and receive mentorship from senior engineers during in-person surges.