Senior Staff Engineer — Data Engineering & Architecture

Ripple
San Francisco, CA, United StatesPosted 27 March 2026

Job Description

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. At Ripple, we're building a world where value moves like information does today. It's big and bold, and we're already doing it. Through our crypto solutions for financial institutions, businesses, governments, and developers, we improve the global financial system. We craft greater economic fairness and opportunity for more people in more places globally. We perform the best work of our careers and develop our skills with colleagues who have our backs. If you're ready to see your impact and embrace meaningful new challenges, join us, and build real world value. The Work: We're seeking a Senior Staff Engineer to act as the technical architect and strategic leader for Ripple's data platform. This role is one of the highest-impact individual contributor positions on the Data team. You will build a coherent, unified view of Ripple's data across all business units. You will establish the definitive source of truth for company metrics and lead our "AI for Data" transformation. You will collaborate across data teams and work directly with senior leadership in Data, Product, Engineering, and Go-to-Market to develop how Ripple understands itself through data. You won't just build systems; you will define the technical vision that connects them. This sits at the intersection of architecture, integration, governance, and applied AI. What you'll do: Build "One View" of Ripple by serving as the main architect for a Unified Data Fabric. Construct a well-rounded view of Ripple's data platforms, pipelines, and tools. Craft the systems and interoperability standards that bring data together across all business units for leadership, product, and GTM teams. Compose and build the Ripple Metrics Store, a definitive, governed layer that serves as the single source of truth for business metrics across all business units. Define metrics governance, ownership models, and validation frameworks. Build and maintain the Metrics Glossary in partnership with the Data Science team, and collaborators crafting a shared language for how Ripple measures its business. Define and lead the AI roadmap for the Data organization setting the vision for how AI transforms the way Ripple builds, governs, and consumes data. Enable conversational analytics and intelligence by architecting AI Agents that allow non-technical collaborators to self-serve insights directly from the data platform. Automate data engineering workflows by encouraging use of AI-powered coding assistants for SQL/ETL generation. Define the standards, validation frameworks, and guidelines for AI-generated code across the team. Lead cross-team build reviews, setting the technical bar for data architecture decisions across the organization. Mentor and up-level engineers across data teams, raising the standard for system building, code quality, and engineering rigor. Act as the main technical consultant to senior leadership across Data, Product, and Engineering regarding long-term technical bets, platform investments, and build-vs-buy decisions. What you'll bring: 14+ years of experience in data engineering, data architecture, or related software engineering fields, with a significant portion spent in senior technical leadership or architect roles. Having a track record of bringing together data ecosystems from multiple business units, you have built the connections that convert isolated da ... (truncated, view full listing at source)
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