Enterprise Data Architect- Azure Databrick - AI (Richmond)
Capgemini, Richmond, VA, United States
The
Enterprise Data Architect
is responsible for defining and evolving a modern, Databricks‑centric data and AI architecture supporting customer, consumer, manufacturing, and supply chain domains. This role focuses on designing scalable, high‑performance 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 cloud‑native data platforms, accelerate AI innovation, and enable data‑driven decision‑making across the enterprise.
Location :
Onsite -Richmond, Virginia, United States
Key Responsibilities
Define and maintain enterprise data architecture principles, reference architectures, and future‑state roadmaps with a strong emphasis on
Databricks and AI enablement
Design end‑to‑end 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 Databricks‑based data and AI solutions
Lead evaluation, selection, and adoption of cloud‑based data, analytics, and AI technologies, with Databricks as the core platform
Design architectures that support secure, resilient, and high‑performance 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 AI‑driven business outcomes
Technology Stack (Representative)
Cloud Platforms
Microsoft Azure
Architecture Patterns
Lakehouse Architecture (Databricks‑centric)
Data Mesh
Event‑Driven Architecture
Data & Analytics Platforms
Databricks (Primary Platform)
Snowflake
Azure Synapse Analytics
Integration & Streaming
Apache Kafka
Azure Event Hubs
API Management
AI & Advanced Analytics Focus
Define and implement enterprise AI and advanced analytics architectures using
Databricks ML and AI capabilities
Hands‑on 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 large‑scale 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
The base compensation range for this role in the posted location is: $188,000 to $202,000.
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees.
In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility
Important Notice:
Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Enterprise Data Architect
is responsible for defining and evolving a modern, Databricks‑centric data and AI architecture supporting customer, consumer, manufacturing, and supply chain domains. This role focuses on designing scalable, high‑performance 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 cloud‑native data platforms, accelerate AI innovation, and enable data‑driven decision‑making across the enterprise.
Location :
Onsite -Richmond, Virginia, United States
Key Responsibilities
Define and maintain enterprise data architecture principles, reference architectures, and future‑state roadmaps with a strong emphasis on
Databricks and AI enablement
Design end‑to‑end 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 Databricks‑based data and AI solutions
Lead evaluation, selection, and adoption of cloud‑based data, analytics, and AI technologies, with Databricks as the core platform
Design architectures that support secure, resilient, and high‑performance 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 AI‑driven business outcomes
Technology Stack (Representative)
Cloud Platforms
Microsoft Azure
Architecture Patterns
Lakehouse Architecture (Databricks‑centric)
Data Mesh
Event‑Driven Architecture
Data & Analytics Platforms
Databricks (Primary Platform)
Snowflake
Azure Synapse Analytics
Integration & Streaming
Apache Kafka
Azure Event Hubs
API Management
AI & Advanced Analytics Focus
Define and implement enterprise AI and advanced analytics architectures using
Databricks ML and AI capabilities
Hands‑on 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 large‑scale 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
The base compensation range for this role in the posted location is: $188,000 to $202,000.
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees.
In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility
Important Notice:
Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.