Enterprise Data Architect

Job Summary

The Enterprise Data Architect is responsible for defining and evolving a modern, Databrickscentric data and AI architecture supporting customer, consumer, manufacturing, and supply chain domains. This role focuses on designing scalable, highperformance data and AI platforms that enable advanced analytics, machine learning, and generative AI solutions aligned with business strategy. The architect partners closely with business, analytics, and technology leaders to drive adoption of cloudnative data platforms, accelerate AI innovation, and enable datadriven decisionmaking across the enterprise.

Role

• Define and maintain enterprise data architecture principles, reference architectures, and futurestate roadmaps with a strong emphasis on Databricks and AI enablement
• Design endtoend data and AI architectures, including data ingestion, lakehouse storage, processing, analytics, machine learning, and generative AI workflows
• Act as a strategic partner to business, analytics, and IT stakeholders to translate business objectives into scalable Databricksbased data and AI solutions
• Lead evaluation, selection, and adoption of cloudbased data, analytics, and AI technologies, with Databricks as the core platform
• Design architectures that support secure, resilient, and highperformance AI and analytics workloads at enterprise scale
• Identify and implement automation opportunities across data pipelines, ML workflows, and AI production deployments
• Introduce and apply emerging technologies and innovative architecture patterns to accelerate AIdriven business outcomes
• Define and implement enterprise AI and advanced analytics architectures using Databricks ML and AI capabilities
• Handson experience with machine learning platforms, MLOps pipelines, feature engineering, and model deployment
• Strong understanding of Generative AI, Large Language Models (LLMs), vector search, and AI application architectures
• Apply AI solutions to:
  • Demand planning and forecasting
  • Customer and consumer insights
  • Intelligent manufacturing
  • Supply chain optimization

Required Qualifications

• Bachelor s or master s degree in Computer Science, Engineering, or a related field
• 12-16+ years of experience in enterprise data architecture and largescale data platforms
• Deep domain experience in customer, manufacturing, or supply chain data ecosystems
• Proven ability to lead data and AI architecture initiatives and influence senior technical and business stakeholders
• Strong communication skills with the ability to articulate complex AI and data concepts to executive leadership
• Capgemini Architects certification level 3 or above, relevant data architecture certifications, IAF andoror industry certifications such as TOGAF 9 or equivalent.

Technology Stack (Representative)

Cloud Platforms

• Microsoft Azure

Architecture Patterns

• Lakehouse Architecture (Databrickscentric)
• Data Mesh
• EventDriven Architecture

Data & Analytics Platforms

• Databricks (Primary Platform)
• Snowflake
• Azure Synapse Analytics

Integration & Streaming

• Apache Kafka
• Azure Event Hubs
• API Management