VP, Business Data Delivery

VP, Business Data Delivery

LendingClub (soon to be Happen Bank) 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

The VP, Business Data Delivery is responsible for delivering trusted, business-ready data products that power decision-making across LendingClub—from Marketing, Personal Loans, Deposits, Credit Risk, Fraud, Operations, and Compliance. This leader owns the data engineering, analytics engineering, data product management, and customer data delivery capabilities that translate business priorities into measurable outcomes. Partnering closely with business leaders and the VP, Data Platforms, this role defines how customer, product, and operational data is transformed into actionable insights, analytics, AI-enabled experiences, and decisioning capabilities. Driven by LendingClub's mission of improving the financial health of everyday Americans, the VP will build a data-driven culture, shape the company's customer data strategy, and lead the teams responsible for turning data into measurable business value.

Business Data Strategy & Product Delivery

• Define and execute the strategy and roadmap for business-facing data products that support Marketing, Lending, Credit Risk, Fraud, Operations, Deposits, and Compliance
• Lead the delivery organization across Data Engineering, Analytics Engineering, Data Product Management, and Data Science
• Partner with business leaders to translate strategic priorities into scalable data products and measurable outcomes
• Establish operating models that ensure data investments align with business value, adoption, and business outcomes
• Lead the Data Product Management practice, including intake management, prioritization frameworks, delivery governance, and the operating model between business stakeholders and delivery teams

Customer Data & Activation

• Own the end-to-end customer data product strategy, including customer, product, and behavioral data integration
• Deliver trusted customer data capabilities that power marketing activation, personalization, credit and fraud decisioning, collections strategy, and operational intelligence
• Lead Customer Data Platform (CDP) initiatives, identity resolution capabilities, and downstream activation across business functions
• Partner with business teams to evolve the customer data strategy and ensure a unified customer view across the enterprise

Analytics, AI & Business Insights

• Define the strategy for business-facing analytics, AI enablement, and self-service data products
• Lead analytics initiatives that directly support business outcomes and prepare data products for AI and machine learning use cases
• Drive adoption of AI-assisted data discovery, automated insight generation, and GenAI-powered self-service capabilities
• Enable advanced analytics and machine learning through high-quality, business-ready data products that accelerate decision-making

Data Quality, Governance & Delivery Excellence

• Establish standards for data quality, certification, testing, QA, and governance throughout the data product lifecycle
• Ensure business confidence in data products through robust validation, monitoring, and delivery processes
• Partner closely with the VP, Data Platforms to align delivery capabilities with platform strategy, architecture, and engineering standards
• Promote strong data practices and ensure data requirements are incorporated early in product and business planning processes

Leadership & Business Partnership

• Build a data-driven culture by embedding data product management and analytics capabilities close to the business and holding teams accountable for outcomes, not output
• Lead and develop high-performing teams across Data Engineering, Analytics Engineering, Data Product Management, and Data Science
• Foster a culture of accountability, innovation, collaboration, and continuous improvement
• Attract, coach, mentor, and retain exceptional technical, analytical, and product talent
• Serve as a trusted advisor to executive leadership on data strategy, customer data, analytics, and AI opportunities

About You

• 13+ years of data engineering, analytics engineering, data product management, or related technology experience, including 10+ years leading and developing teams across data engineering, analytics, and data product management
• 5+ years leading large-scale data products, customer data platforms, analytics organizations, or business-facing data delivery functions in a public cloud environment
• Demonstrated experience building data products and services that support customer experiences, marketing activation, credit decisioning, fraud detection, operations, and business intelligence
• Experience leading customer data delivery, Customer Data Platform programs, identity resolution capabilities, and downstream activation use cases
• Strong understanding of modern data architectures, customer data platforms, analytics ecosystems, and data product operating models
• Experience leading Data Engineering, Analytics Engineering, Data Product Management, or Data Science organizations
• Ability to translate business objectives into data product strategies and measurable outcomes
• Strong executive communication skills with the ability to influence business, technology, and regulatory stakeholders
• Experience promoting data literacy and building data-driven cultures across technical and non-technical organizations
• Strong understanding of modern data tooling and ecosystems, including lakehouse platforms (Databricks preferred), transformation tooling (dbt), BI platforms (Tableau), and cloud-native data architectures
• Hands-on familiarity with advanced analytics, machine learning, and AI-enabled business capabilities
• Experience operating within highly regulated industries such as financial services, healthcare, or similar environments
• Ability to deliver value quickly and incrementally while balancing strategic objectives and business priorities
• Bachelor's degree or higher; or equivalent combination of education and work experience

Nice to Have

• Experience working in both high-growth organizations and large-scale enterprises
• Understanding of consumer financial products, personal financial management, lending, deposits, fraud, or risk domains
• Experience building data products for credit risk, fraud, collections strategy, marketing, or operations analytics
• Experience with AWS and modern cloud-native data ecosystems
• Experience leading enterprise AI enablement initiatives and modern data product transformations
• Proven ability to attract, hire, and develop exceptional technical and product talent