Data Platform Architect

Data And AI Platform Architect

Happen Bank (formerly LendingClub) is built around a simple purpose: to clear the way to help people turn intention into action, and action into financial progress. That means offering focused products, a frictionless mobile-first experience, and clear terms with no gotchas. Respect and fairness is part of our DNA, and that ideal shapes how we work, how we treat each other, and how we invest in our employees and our community. Join us in using data, bold thinking, and a commitment to innovation to help clear the way for millions of Americans to achieve more.

About the Role

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.

What You'll Do

• Define and maintain the reference architecture for Happen Bank'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 or higher, or equivalent combination of education and 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 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'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

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