Senior Staff Engineer — Data Engineering & Architecture

About Us

At Ripple, we're building a world where value moves like information does today. 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.

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.

• 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.

• 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.
• Track record of bringing together data ecosystems from multiple business units, having built the connections that convert isolated data platforms into a consistent entity.
• Deep expertise in modern data architecture, data mesh, lakehouse patterns, with hands-on experience in technologies like Spark, Kafka, Airflow, dBT, Databricks, and cloud-native data services (AWS, GCP, or Azure).
• Experienced in metrics governance and semantic layers, having established or planned metrics stores, business glossaries, or comparable systems that provide an organization's source of truth.
• Demonstrated experience with AI/ML in data engineering contexts, whether building feature stores, deploying AI-powered data quality monitoring, integrating LLMs into developer workflows, or crafting agentic systems for data operations.
• Architectural vision paired with execution ability, capable of whiteboarding a multi-year platform strategy and also getting into the code to prototype critical path components.
• Outstanding communication and influence skills, comfortable presenting to VP/C-level audiences. Ability to translate technical trade-offs into business language and build consensus among teams with competing priorities.
• Collaborative, ego-free approach to leadership, leading through influence and technical credibility, not through title.
• BS or equivalent experience in Computer Science or similar.

• Experience with blockchain data, on-chain analytics, or large-scale financial/payments data.
• Direct involvement with LLM-enabled developer tools and agents, AI code synthesis, RAG-style data catalogs, natural language querying interfaces, or agent orchestration solutions.

For positions based in CA, the annual salary range for this position is $232,000 USD - $280,000 USD. Actual salaries may vary based on numerous factors including an individual applicant’s experience and qualifications. This range does not include equity or…