Director- Data Architect- Databrick - AI

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

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.