Data Platform Architect

Current Employees of LendingClub: Please apply via your internal Workday account. About the Role This role defines the technical architecture for 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 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. What You’ll Do 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. 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. Operate as a technical authority across teams – your architecture decisions are respected because they are grounded in deep expertise, operational awareness, and a clear accounting of trade-offs. 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. Understand how to apply AI to complex, high‑stakes platform architecture – not just for efficiency, but to unlock better outcomes. Set a high bar for responsible use, including attention to data integrity, model limitations, and compliance considerations, and build new architectural workflows, not just iterate on existing ones. Build with AI, not just use it – 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. Collaborate naturally across organizational boundaries – work with infrastructure, security, integration, DevOps, and governance teams as a connector, not a gatekeeper. Communicate architecture decisions in business terms, making complex trade‑offs understandable to engineering leaders, compliance stakeholders, and executive sponsors. Nice to Have 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. Location & Work Model San Francisco – eligible offices for this role. We utilize a hybrid work model with in‑office Tuesdays, Wednesdays, and Thursdays. In‑person attendance is essential for this role’s success; remote placement will not be considered. Compensation & Benefits Target base salary range: $210,000 – $245,000. Additional compensation may include long‑term awards (equity) and an annual bonus based on company and employee performance. Benefits include medical, dental, and vision plans for employees and families; 401(k) match; health and wellness programs; flexible time off; up to 16 weeks paid parental leave; and more. Time Zone & Travel Primarily Pacific Time (PT). The position will primarily work local hours, but the ideal candidate will be flexible working across time zones when necessary. Travel to LendingClub offices and/or other locations as needed. Equal Opportunity Statement LendingClub is an equal opportunity employer and dedicated to diversity, equity, and inclusion in the workplace. We do not discriminate on the basis of race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), gender, gender identity, gender expression, sexual orientation, age, marital status, veteran status, disability status, political views or activity, or other applicable legally protected characteristics. We believe that a variety of perspectives will make our teams and business stronger as we work together to transform the traditional banking system. We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, please contact us at View email address on click.appcast.io. #J-18808-Ljbffr