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.

Analytics Engineer - Compliance Data

As an Analytics Engineer on the Compliance Data team within Platform, you'll build and maintain the production-grade data foundations that every regulatory obligation at Coinbase depends on. This team owns the Compliance Data Mart (CDM), Coinbase's canonical source of truth for user, transaction, and compliance data. You'll own the full lifecycle of data models and pipelines that downstream reporting, analytics, and AI workflows all build on, while also delivering accurate, timely data when regulators come calling.

What you'll do:

Own end-to-end development of production-grade data models and pipelines at the core of the CDM, covering user, transaction, and compliance data across retail and institutional product lines, from architecture through deployment and maintenance.

Build data quality checks, data contracts, validation logic, and monitoring that protect data integrity before issues propagate to downstream reports or workflows.

Partner with upstream engineering teams to fix data gaps and absorb product changes at the source, taking accountability for data issues anywhere in the stack rather than passing them downstream.

Support live regulatory exams, audits, and ad hoc regulator requests with accurate, timely data, balancing time-sensitive reactive work with long-term foundational projects.

Automate recurring manual workflows into scalable pipelines and self-serve tooling, enabling downstream teams and AI agents to answer their own questions.