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.

Benefits

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architecturedata modelingdata warehousingdata lakesdata martsdata integrationdata lifecycle managementAI architectural patternsMLOpsdata as a product

Soft Skills

analytical skillsproblem-solving skillsorganizational skillssystem design skillscollaborationstakeholder alignmentleadershipcommunication

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in Information TechnologyBachelor's degree in Data ScienceMaster's degreeCDMPCIMP