Chief Data and AI Officer

Key Responsibilities

• Build, lead, and mentor high-performing teams across IT operations, cybersecurity, infrastructure, applications, data engineering, analytics, and AI functions.
• Foster a culture of innovation, accountability, collaboration, inclusion, and continuous improvement.
• Lead organizational change management efforts that support enterprise transformation and technology adoption.
• Develop succession planning and leadership development programs for critical roles.
• Develop and execute a multi-year enterprise technology strategy aligned with organizational growth, operational excellence, and long-term business objectives.
• Serve as the primary technology advisor to the CEO, executive leadership team, and Board of Directors on digital innovation, cybersecurity, AI, data strategy, and technology investments.
• Translate complex technical concepts into clear business value, measurable ROI, and strategic outcomes.
• Lead enterprise-wide modernization initiatives that improve productivity, collaboration, operational efficiency, and profitability.
• Lead large-scale digital transformation initiatives across construction operations, field technology, enterprise systems, and corporate platforms.
• Modernize legacy systems and drive adoption of cloud-native, scalable, and integrated technology ecosystems.
• Partner with business leaders to identify and implement technology-enabled process improvements and automation opportunities.
• Evaluate emerging technologies including Generative AI, machine learning, IoT, predictive analytics, robotics, and intelligent automation.
• Develop and execute an enterprise-wide AI and data strategy that positions data as a strategic organizational asset.
• Establish scalable data governance, architecture, analytics, and business intelligence capabilities that support informed decision-making at all levels of the organization.
• Drive deployment of AI and machine learning solutions that improve forecasting, operational performance, risk management, workforce productivity, and project delivery outcomes.
• Ensure ethical, secure, and compliant use of AI technologies and enterprise data assets.
• Oversee enterprise applications including ERP, HRIS, CRM, project management, collaboration, and construction technology platforms.
• Lead cloud strategy and infrastructure management across hybrid and multi-cloud environments.
• Ensure enterprise systems deliver high availability, scalability, reliability, performance, and security.
• Drive adoption of modern engineering practices including Agile, DevOps, automation, and platform standardization.
• Establish KPIs and performance metrics that measure technology effectiveness, operational impact, cybersecurity posture, and business value realization.
• Optimize technology spend while supporting innovation and organizational scalability.

AI, Data & Analytics Leadership

• Develop and execute an enterprise-wide AI and data strategy that positions data as a strategic organizational asset.
• Establish scalable data governance, architecture, analytics, and business intelligence capabilities that support informed decision-making at all levels of the organization.
• Drive deployment of AI and machine learning solutions that improve forecasting, operational performance, risk management, workforce productivity, and project delivery outcomes.
• Ensure ethical, secure, and compliant use of AI technologies and enterprise data assets.