Enterprise Data Architect

Role Summary

The Enterprise Data Architect is responsible for defining, governing, and evolving the enterprise-wide data architecture strategy across customer, consumer, manufacturing, and supply chain domains. This role ensures alignment between business strategy, data platforms, analytics, and emerging AI capabilities, while driving scalability, security, and standardization across the organization.

Key Responsibilities

• Define enterprise data architecture principles, standards, and target-state roadmaps
• Design end-to-end data architectures covering data ingestion, storage, processing, analytics, and AI
• Partner with business, analytics, and technology leaders to translate strategic objectives into scalable data solutions
• Provide architectural governance across multiple programs and initiatives
• Establish standards for:
  • Data integration
  • Master Data Management (MDM)
  • Metadata management
  • Data quality
• Evaluate, select, and standardize cloud-based data and analytics platforms
• Ensure compliance with security, privacy, regulatory, and resiliency requirements
• Identify and implement automation opportunities across data processes
• Introduce and implement emerging technologies and innovative data concepts

Technology Stack (Representative)

Cloud Platforms

• Azure

Architecture Patterns

• Lakehouse
• Data Mesh
• Event-Driven Architecture

Data Platforms

• Snowflake
• Azure Synapse
• Databricks

Integration & Streaming

• Kafka
• Event Hubs
• API Management

Analytics & BI

• Power BI
• Tableau
• Looker

Governance & Security

• Microsoft Purview
• Collibra
• Identity & Access Management (IAM)
• Encryption frameworks

AI & Advanced Analytics (Preferred)

• Define enterprise AI and advanced analytics architectures
• Experience with ML platforms, MLOps, and AI lifecycle governance
• Understanding of generative AI, large language models (LLMs), and responsible AI practices
• Apply AI solutions to:
  • Demand planning
  • Customer insights
  • Intelligent manufacturing
  • Supply chain optimization

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 12–16+ years of experience in enterprise data architecture
• Strong domain experience in customer, manufacturing, or supply chain environments
• Proven ability to influence stakeholders and lead architecture governance initiatives