About this role

▸about Paxos — company background

Applying to Paxos? Our only careers site is paxos.com/careers, and we only recruit via @paxos.com email. Details below. ___

About Paxos

Today’s financial infrastructure is archaic, expensive, inefficient and risky — supporting a system that leaves out more people than it lets in. So we’re rebuilding it.

We’re on a mission to open the world’s financial system to everyone by enabling the instant movement of any asset, any time, in a trustworthy way. For over a decade, we’ve built blockchain infrastructure that tokenizes, custodies, trades and settles assets for the world's leading financial institutions, like PayPal, Venmo, Mastercard, Interactive Brokers and Charles Schwab.

About the team

The Data Engineering team at Paxos builds and maintains the data infrastructure that powers our engineering partners and analytics teams, providing scalable, reliable, and secure data access for product analytics, business intelligence, client and regulatory reporting, and operational efficiencies. You'll join a small, high-impact group of engineers across US and India time zones, working with teams across the company to continuously enhance our data platform, driving innovation, optimizing costs, and unlocking new revenue opportunities.

About the role

The Data Platform Engineer at Paxos serves as an owner of key parts of our data platform, from design through production operation. Depending on the problem, your work may span data pipelines, streaming systems, data lakes and warehouses, databases, Kubernetes, cloud infrastructure, automation, security, or governance. You will turn ambiguous needs into reliable, maintainable systems and take responsibility for their operational outcomes. We're looking for strong engineering fundamentals, deep experience in at least one relevant area, sound technical judgment, and the ability to learn unfamiliar systems quickly. You don't need experience with every part of our stack: a strong engineer with Spark experience is welcome even though we don't currently use it, because what matters is how you've designed, scaled, and operated data systems.

What you’ll do

Own data-platform projects end to end: clarify the problem, evaluate alternatives, design the system, implement and roll it out safely, document it, and operate it in production.