Senior Director, Data & AI

What success looks like in this role:

• Define the global Data & AI vision, strategy, and multi-year roadmap, aligned to company growth, profitability, and client-outcome goals.
• Set the technology direction across data platforms, engineering, integration, analytics, machine learning, generative AI, and agentic AI.
• Make data readiness the foundation for AI: guide clients and internal teams to modern, well-governed data estates before and alongside AI adoption.
• Track market trends, hyperscaler and partner roadmaps, regulation, and emerging technology, and turn them into clear investment priorities.
• Sponsor innovation through pilots, proofs of concept, and accelerators, and move proven ideas into production and repeatable practices.

• Own the delivery of Data & AI engagements, including data modernization, data engineering, analytics, machine learning, generative AI, and agentic AI solutions, from design through production.
• Set delivery standards for quality, security, cost, and timelines, and step in on high-risk or strategic engagements.
• Establish reusable methods, accelerators, reference architectures, and tooling so teams deliver faster and more consistently.
• Build and run the operating model for data and AI in production, including MLOps, monitoring, support, and continuous improvement.
• Work with Delivery, Engineering, and Forward Deployed teams to share resources, skills, and lessons learned across engagements.

• Set architecture principles for secure, scalable, and cost-efficient data and AI platforms across cloud and hybrid environments.
• Establish data governance practices covering data quality, lineage, privacy, security, and regulatory compliance.
• Define responsible-AI policies and testing standards, including bias, explainability, safety, and human oversight, and apply them before AI is used with clients.
• Work with Security, Legal, and Compliance on risk, intellectual property, and data-protection requirements for each market.

• Act as a senior advisor to client executives on data and AI strategy, and build long-term relationships that lead to repeat and expanded work.
• Support Sales and Presales on strategic pursuits, including solution shaping, orals, workshops, and delivery risk.
• Build and manage strategic relationships with hyperscalers, data and AI platform vendors, and alliance partners.
• Contribute to pricing, estimation, and commercial models for Data & AI work, working with Finance and Pricing.
• Represent the company at industry events, with analysts, and in the market as a Data & AI thought leader.

• Own revenue, margin, utilization, and budget targets for the Data & AI organization, and report performance to senior leadership.
• Plan capacity and hiring against demand, balancing employees, contractors, and partners.
• Manage delivery, financial, and security risk, with clear escalation paths.
• Set clear decision rights and ways of working with Sales, Delivery, Engineering, Architecture, Finance, Marketing, and shared functions.

• Build and lead a high-performing global team of data engineers, data scientists, AI engineers, architects, and consultants, including managers and senior technical leaders.
• Hire, develop, and retain top talent, with clear career paths, succession plans, and a culture of continuous learning.
• Set skills and certification goals across data platforms, machine learning, generative AI, and agentic AI.
• Coach leaders and teams on technical excellence, client engagement, and executive communication.
• Align organization structure, skills, and ways of working to support rapid innovation and growth.

You will be successful in this role if you have:

• 15+ years of experience in data, analytics, AI, or technology consulting, including 8+ years leading large, global technical teams.
• Deep technical knowledge across modern data platforms, data engineering, analytics, machine learning, generative AI, and agentic AI, with solutions taken from design into production.
• Hands-on understanding of cloud data platforms and AI services from the major hyperscalers (such as AWS, Microsoft Azure, and Google Cloud), and of data governance, security, and responsible-AI practices.
• Track record of delivering large, complex Data & AI programs on time, on budget, and to quality standards.
• Experience owning financial targets such as revenue, margin, utilization, and budget.
• Strong…