Vice President, Strategic Data Architecture

Role Overview

• Establish and maintain the enterprise data architecture vision, including conceptual, logical and physical models, data flows, storage patterns, and integration frameworks
• Create and maintain a comprehensive inventory of current state data capabilities across all business units
• Define the target state architecture and align stakeholders on the required data product capabilities and technical foundations
• Define and integrate already architectural patterns that support enterprise AI, Generative AI, and Agentic AI use cases, ensuring scalable and governed deployment across the ecosystem
• Partner closely with leaders across Data Management, Data Governance, Data Product, Data Engineering, Analytics, and Product teams to translate business needs into data driven solutions
• Collaborate with AI/ML teams to shape enterprise AI strategies, ensuring data architecture enables model development, model operations (MLOps), vector storage, retrieval augmented generation (RAG), and agent-oriented workflows
• Identify opportunities to simplify, consolidate, or modernize legacy technologies, data stores, and applications
• Oversee the design of scalable architectures that support enterprise-wide data products and shared capabilities across multiple business units and group-level functions
• Lead the development and enforcement of data architecture standards, quality frameworks, and governance policies
• Incorporate AI governance standards, including model transparency, lineage, auditability, responsible AI practices, and controls for Generative AI and Agentic AI solutions
• Stay current with emerging technologies, architecture patterns, and industry best practices.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field
• Master’s degree or relevant professional certifications (e.g., CDMP, CIMP) strongly preferred
• 10+ years of experience in data management, data governance, or related disciplines within SaaS or cloud based environments
• Extensive background in enterprise data architecture, cloud solutions, data modeling, data warehousing, data lakes, data marts, and BI ecosystems
• Proven success designing and implementing architectures that deliver data as a product for internal and external stakeholders
• Strong understanding of structured and unstructured data management, data integration, data lifecycle management, and modern data platforms
• Experience working with Scaled Agile or similar methodologies
• Proficiency in AI architectural patterns, data preparation for AI/ML, and designing systems that support LLMs and Agentic AI workflows
• Expertise in cloud data platforms and tools (e.g., AWS, Snowflake, Redshift, Azure, Google Cloud, MDM, ETL/ELT tools)
• Deep knowledge of data governance frameworks, data management principles, and industry standards (ISO 27001, SOC 2)
• Strong understanding of data privacy and compliance requirements (GDPR, CCPA, emerging AI related)
• Advanced analytical, problem-solving, organizational, and system design skills.

Tech Stack

• Amazon Redshift
• AWS
• Azure
• Cloud
• ETL

Benefits

• health insurance (medical, dental, vision)
• a retirement savings plan
• paid time off
• other employee benefits