Data Architect

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The Data Architect is responsible for designing, developing, and governing the enterprise data architecture that enables reliable, secure, scalable, and accessible data across the organization. This role establishes the frameworks, standards, models, and integration patterns that define how data is collected, structured, stored, integrated, governed, and consumed across business applications and analytics platforms.

The Data Architect serves as a strategic and technical partner to business leaders, IT, application teams, data and analytics teams, and external partners. The role is particularly important in an environment with multiple business units, brands, locations, ERP platforms, and acquired or integrated businesses.

The successful candidate will balance long-term enterprise architecture with practical business needs, helping the organization improve data quality, simplify its technology landscape, strengthen governance, and establish a trusted foundation for reporting, analytics, automation, and artificial intelligence.

• Develop and maintain the enterprise data architecture strategy, standards, principles, and roadmaps aligned with business and technology objectives.
• Design scalable data architectures across cloud, on-premise, and hybrid environments supporting structured and unstructured data.
• Define current and future-state architectures, reduce complexity and technical debt, and establish patterns for data ingestion, storage, integration, transformation, consumption, and retention.
• Evaluate emerging technologies and ensure architecture decisions enable future capabilities in analytics, AI, machine learning, and automation.

Data Modeling & Design

• Develop and govern conceptual, logical, and physical data models supporting enterprise applications, reporting, analytics, and integrations.
• Establish enterprise data standards, definitions, canonical models, metadata, lineage, retention, and lifecycle management practices.
• Partner with business and technical teams to identify authoritative data sources and ensure models support both operational and analytical needs.
• Provide architecture leadership for SAP S/4
  
  HANA and other enterprise platforms, including finance, HR, CRM, manufacturing, supply chain, and e-commerce systems.
• Define integration standards and data exchange frameworks across applications, acquired businesses, legacy systems, and external partners.
• Support implementations, migrations, conversions, and transformation initiatives while ensuring cross-functional business processes are effectively integrated.

Data Governance & Quality

• Define data ownership, stewardship, and accountability while implementing controls that ensure data quality, consistency, accuracy, completeness, and timeliness.
• Develop processes to identify and resolve systemic data issues and maintain enterprise metadata, lineage, data catalogs, and business glossaries.

Data Integration & Analytics Enablement

• Define architecture standards for APIs, data pipelines, ETL/ELT processes, warehouses, lakes, and analytics platforms.
• Collaborate with reporting and analytics teams to ensure data is structured, governed, and accessible for enterprise reporting and self-service analytics.
• Promote reusable integration patterns and reduce redundant data repositories and point-to-point integrations.

AI & Advanced Analytics Readiness

• Establish data architecture requirements that support AI, machine learning, predictive analytics, and generative AI initiatives.
• Assess data readiness for business use cases and ensure AI solutions leverage secure, governed, accurate, and traceable enterprise data from multiple sources.

Security, Privacy & Risk

• Collaborate with cybersecurity, legal, privacy,