Data Platform Architect

• This role defines the technical architecture our data and AI platform - the shared infrastructure that powers origination, marketing, credit decisioning, analytics, and AI capabilities across every business domain
• You will set architecture standards, design resilient patterns, and govern platform technology choices that must align across multiple CIO and CPTO teams, while partnering closely with Data & AI Platform Engineering to ensure designs translate into production-grade, cost-efficient systems
• 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

Benefits

• Untracked vacation for salaried employees, which means take it when you need it, and generous paid time off for hourly team members
• A hybrid work model that balances in-office and work from home
• Leading health and safety protocols related to COVID, including complimentary at-home testing kits from Cue Health for those coming to the office
• Up to 16 weeks paid leave for new parents, plus a fully paid, phased return-to-work policy for qualified leaves
• Mothers Rooms and hospital-grade pumps in every LC office
• Generous and varied mental health benefits
• Wellness program with cash incentives — earn up to $75 per month for being active
• Paid volunteer time and donation matching
• Onsite gym, locker room, bike room, and fitness classes (depending on location)
• Café with our own in-house barista
• Stocked pantries with healthy snacks and drinks
• Technology-forward and collaborative office spaces

Preferred experience

• 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
• 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
• 12+ years of experience in data engineering, data architecture, or platform engineering; bachelor’s degree in a related field or equivalent work experience
• You collaborate naturally across organizational boundaries - working with infrastructure, security, integration, DevOps, and governance teams as a connector, not a gatekeeper
• 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 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 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 communicate architecture decisions in business terms, making complex trade-offs understandable to engineering leaders, compliance stakeholders, and executive sponsors
• 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