VP, Enterprise Data Platform

At Early Warning, we've powered and protected the U.S. financial system for over thirty years with cutting-edge solutions like Zelle , Paze , and so much more. As a trusted name in payments, we partner with thousands of institutions to increase access to financial services and protect transactions for hundreds of millions of consumers and small businesses.

Positions located in Scottsdale, San Francisco, Chicago, or New York follow a hybrid work model to allow for a more collaborative working environment.

Candidates responding to this posting must independently possess the eligibility to work in the United States, for any employer, at the date of hire. This position is ineligible for employment Visa sponsorship.

Overall Purpose

This role is accountable for defining, building, and operating the enterprise data platform, including Lakehouse architecture, AI/ML platform capabilities, and analytics foundations. The Vice President establishes the long-term technical vision and leads execution of a scalable, secure, and governed platform that enables high-value data products and enterprise insights.

This position operates at an enterprise level, setting architectural direction, driving platform modernization, and ensuring alignment with regulatory, security, and business requirements. The role balances strategic planning with delivery accountability, enabling petabyte-scale data processing, real-time and batch data integration, and trusted data consumption across the organization.

Essential Functions

Data Platform Engineering

• Define and own the target-state architecture for the enterprise data platform, including Lakehouse, streaming, batch processing, semantic layers, and AI/ML platform capabilities
• Establish and maintain a multi-year roadmap that balances scalability, resilience, regulatory compliance, and business value delivery
• Drive architectural standards, patterns, and reference implementations to enable consistent and reusable platform capabilities
• Lead the design, build, and operation of high-throughput, highly available data platforms supporting petabyte-scale workloads
• Ensure platform capabilities support real-time and batch ingestion, transformation, storage, and consumption across enterprise use cases
• Enable scalable support for analytics, reporting, data products, and machine learning lifecycle requirements

Technology Modernization

• Lead transformation from fragmented and siloed data environments to a unified, governed platform
• Introduce modern architectural patterns, engineering practices, and operating models that improve platform scalability, reliability, and usability
• Drive adoption of platform services and reduce duplication across teams
• Establish enterprise standards for data quality, lineage, metadata, cataloging, observability, and lifecycle management
• Ensure platform design and operations meet security, privacy, and regulatory requirements, particularly for sensitive and PII data
• Partner with Security, Risk, and Compliance functions to align with enterprise governance frameworks (e.g., SOC 2 and related controls)

Organizational Leadership & Influence

• Drive enterprise adoption of platform services and data product capabilities
• Build and lead high-performing platform engineering organizations, including senior leaders and architects
• Establish a culture of ownership, engineering excellence, and operational discipline
• Develop leadership bench strength and ensure organizational scalability
• Partner with Data Science, Product, Engineering, Security, Risk, and business stakeholders to align platform capabilities with enterprise priorities
• Enable use cases across analytics, AI/ML, product intelligence, and operational reporting

Minimum Qualifications

• Bachelor's degree in computer science, Engineering, or related field; advanced degree preferred
• 15+ years of experience in data engineering, platform engineering, or distributed systems, including significant leadership experience
• Demonstrated success leading enterprise-scale data platform strategy, architecture, and transformation initiatives
• Deep expertise in modern data architectures (Lakehouse, data lake, data warehouse, or hybrid models)
• Strong technical…