About this role

▸about Coinbase — company background

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.

The Data Platform team builds and operates the systems that centralize all of Coinbase's internal and third-party data, making it easy for teams across the company to access, process, and transform that data for analytics, machine learning, and powering end-user experiences. As an engineer on the team you'll contribute across the full spectrum of our systems, from foundational processing and storage to scalable pipelines to the frameworks, tools, and internal applications that make data easily and efficiently available.

We have a number of open roles within the Data Platform team, each with a different focus area; read on to see if you'll be a good fit as a Data Engineering Platform Engineer.

This role sits between our platform and the analysts, data scientists, and data engineers who use it every day. You'll build the SDKs, self-service apps, and abstractions that let thousands of pipelines and analyses run without those users needing to understand the plumbing underneath.

What you'll do:

Build clean software abstractions and modular, reusable components that let us support thousands of pipelines and beyond as we scale.

Build and maintain data integration and processing SDKs used by data teams and internal services across Coinbase.

Design and build self-service applications that let analysts and data scientists create, manage, and troubleshoot their own pipelines without deep platform knowledge.

Build tooling for data security and observability: access controls across storage and access layers, data quality tracking, dataset cataloging and lineage, usage auditing.

Work cross-functionally: consult upstream teams on structuring their databases to expose good data APIs, and give downstream data scientists well-designed, well-documented data models and metrics.