About this role

▸about Ripple — company background

At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.

If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value.

Role Overview

At Ripple, we're building a world where value moves like information does today. It's big, it's bold, and we're already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.

If you're ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value.

As a Senior Software Engineer on the Data Engineering team, you are a core builder of the Caspian Data Platform — Ripple's centralized lakehouse that powers analytics, financial reporting, product intelligence, and data-driven operations across every business unit. You own the design and delivery of production-grade pipelines end to end. You raise the engineering bar for the team through code reviews, technical design, and mentorship. You operate with high autonomy on complex, cross-functional data initiatives and bring sound judgment to tradeoffs around performance, cost, reliability, and maintainability.

What you'll do

Design, build, and operate production ETL pipelines on Databricks using Delta Live Tables and Spark, applying medallion architecture patterns across Finance, Payments, Product, and GTM domains.

Own data modeling in different layers — defining governed, reusable table structures that serve as reliable sources of truth for business metrics and downstream consumption.

Drive technical design for projects spanning multiple teams, writing clear design documents that articulate architecture, tradeoffs, and rollout plans.

Build pipeline observability into your work — failure detection, alerting, retry logic, and the operational hygiene that keeps oncall burden low.

Integrate AI tooling into data workflows: agentic systems for pipeline triage, automated code generation for transformations, and natural language interfaces for data access.