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:
Bachelors or masters degree in Computer Science Engineering or a related field
12-16 yearsof 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
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 advan...
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:
Bachelors or masters degree in Computer Science Engineering or a related field
12-16 yearsof 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.