Data Platform Architect at Lendingclub

Define and maintain the reference architecture for LendingClub's modern data and AI platform, ensuring it meets enterprise security, compliance, and scalability requirements
Design architectural patterns for data pipelines, storage, compute, and integration that balance performance, cost, and resilience - and validate that what gets built matches what was designed
Govern shared technology choices for the data platform, aligning decisions across infrastructure architecture, security architecture, enterprise integration architecture, and release engineering / DevOps
Develop and enforce standards for platform adoption that other CIO teams must follow, including data modeling patterns, integration contracts, and security guardrails
Lead proofs of concept and technical evaluations for emerging technologies - including AI/ML infrastructure, GenAI integration patterns, and automation platforms - to inform platform roadmap decisions
Drive architecture governance in partnership with the enterprise architecture team, ensuring data platform decisions are consistent with broader technology strategy and regulatory requirements
Identify opportunities to apply AI to improve architecture workflows, from automated impact analysis and capacity planning to intelligent design pattern recommendation and architecture compliance checking
About You
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 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'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
You collaborate naturally across organizational boundaries - working with infrastructure, security, integration, DevOps, and governance teams as a connector, not a gatekeeper
You communicate architecture decisions in business terms, making complex trade-offs understandable to engineering leaders, compliance stakeholders, and executive sponsors

Data Platform Architect

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