Additional Information
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
Early Warning (zelle) · San Francisco