Data Platform Architect

Join LendingClub as a Data Platform Architect, where you will define the technical architecture for our data and AI platform. You will set architecture standards, design resilient patterns, and govern platform technology choices while partnering closely with Data & AI Platform Engineering. Your role will involve maintaining the reference architecture, designing architectural patterns, governing shared technology choices, and leading proofs of concept for emerging technologies. You will also drive architecture governance in partnership with the enterprise architecture team and identify opportunities to apply AI to improve architecture workflows.

• Definir la arquitectura técnica de la plataforma de datos y AI, estableciendo estándares de arquitectura y patrones resilientes.
• Diseñar patrones arquitectónicos para tuberías de datos, almacenamiento, computación e integración, equilibrando rendimiento, costo y resiliencia.
• Desarrollar y hacer cumplir estándares para la adopción de la plataforma, incluyendo patrones de modelado de datos, contratos de integración y barreras de seguridad.
• You operate as a technical authority across teams - your architecture decisions are respected because they're grounded in deep expertise, operational awareness, and a clear accounting of trade-offs
• You design for production, not for diagrams - your patterns account for failover, scalability, security, and the operational burden on the teams who build and maintain them
• You communicate architecture decisions in business terms, making complex trade-offs understandable to engineering leaders, compliance stakeholders, and executive sponsors
• You collaborate naturally across organizational boundaries - working with infrastructure, security, integration, DevOps, and governance teams as a connector, not a gatekeeper
• You understand how to apply AI to complex, high-stakes platform architecture - not just for efficiency, but to unlock better outcomes. You set a high bar for responsible use, including attention to data integrity, model limitations, and compliance considerations, and you're building new architectural workflows, not just iterating on existing ones
• 12+ years of experience in data engineering, data architecture, or platform engineering; bachelor's degree in a related field or equivalent work experience
• You have designed and delivered modern, cloud-based data platforms at scale (Databricks, Snowflake, or equivalent) and understand the trade-offs between performance, cost, governance, and resilience at the architecture level
• You're building with AI, not just using it - you have strong instincts about where AI capabilities belong in the platform architecture, how to evaluate build vs. buy for AI infrastructure, and what responsible production deployment looks like in a regulated financial environment
• Deep experience with the Databricks ecosystem, including Unity Catalog, Delta Lake optimization, and workspace governance at enterprise scale
• Background in enterprise architecture governance at a regulated financial institution (SOX, GLBA, fair lending data requirements)
• Experience with ML/AI platform architecture, including MLOps patterns, model serving infrastructure, evaluation frameworks, and feature stores
• Familiarity with data mesh or domain-oriented data architecture patterns in large, multi-team organizations