Senior Staff Engineer — Data Engineering & Architecture

Ripple Ripple · Fintech · San Francisco, CA +1 · Engineering

Senior Staff Engineer to architect and lead Ripple's data platform, focusing on a Unified Data Fabric, Metrics Store, and driving an "AI for Data" transformation. The role involves defining the AI roadmap for data, architecting AI Agents for analytics, and automating data engineering workflows using AI-powered coding assistants. It sits at the intersection of architecture, integration, governance, and applied AI.

What you'd actually do

  1. Build "One View" of Ripple by serving as the main architect for a Unified Data Fabric.
  2. 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.
  3. 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.
  4. Enable conversational analytics and intelligence by architecting AI Agents that allow non-technical collaborators to self-serve insights directly from the data platform.
  5. Automate data engineering workflows by encouraging use of AI-powered coding assistants for SQL/ETL generation.

Skills

Required

  • 14+ years of experience in data engineering, data architecture, or related software engineering fields
  • Significant portion spent in senior technical leadership or architect roles
  • Track record of bringing together data ecosystems from multiple business units
  • Deep expertise in modern data architecture, data mesh, lakehouse patterns
  • 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
  • Demonstrated experience with AI/ML in data engineering contexts
  • Architectural vision paired with execution ability
  • Outstanding communication and influence skills
  • Collaborative, ego-free approach to leadership

Nice to have

  • 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

What the JD emphasized

  • architectural vision paired with execution ability
  • AI/ML in data engineering contexts
  • LLM-enabled developer tools and agents, AI code synthesis, RAG-style data catalogs, natural language querying interfaces, or agent orchestration solutions

Other signals

  • AI for Data transformation
  • AI roadmap for Data organization
  • AI Agents for conversational analytics
  • AI-powered coding assistants for SQL/ETL