Data Engineer Intern

Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase.

This is a 12-week internship during summer 2027.

As a Data Engineer Intern within the Platform product group, you'll partner with analytics engineering to build and maintain the data pipelines and infrastructure that power insights across Coinbase. You'll work alongside senior engineers and cross-functional partners in product and engineering to ensure data accuracy, scalability, and accessibility for analytical and machine learning use cases.

What you'll do:

• Build and maintain data pipelines that ensure data integrity and accessibility for analytics and machine learning workloads
• Support the development of scalable data infrastructure using Python and cloud-based technologies
• Integrate and manage data from multiple sources, including internal systems and external APIs
• Contribute to analytical deep dives with senior team members, translating findings into clear documentation and recommendations
• Learn and apply data engineering best practices including data governance, security, and performance optimization

Required Skills and Experience:

• Completed or in-progress coursework in Computer Science, Data Engineering, or equivalent experience with demonstrated programming proficiency in Python, including data structures and algorithms
• Hands-on experience writing SQL for data analysis and working with relational database concepts
• Familiarity with cloud platforms (AWS, GCP, or Azure) and a demonstrated interest in AI, LLMs, or API integrations
• Exposure to software architecture concepts such as microservices, distributed systems, or cloud-native design through coursework or projects
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

Req ID: P78146

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