Lead Consultant - Data Architecture & Engineering

About the role

GHD is seeking a Lead Consultant - Data Architecture & Engineering to join our Americas Business Advisory practice. This role is a senior seller-doer position for a technically deep consulting leader who combines strong market-facing capabilities with hands-on expertise in data architecture, data engineering, and advanced analytics.

Responsibilities

• Lead client engagements, shape and sell new work, and provide technical and delivery leadership across complex data and AI programs.
• Translate business objectives into scalable data architecture, analytics, and AI solutions.
• Facilitate executive workshops and working sessions to define vision, roadmap, and investment priorities.
• Provide hands-on technical leadership in data architecture, data engineering, and analytics solution design.
• Oversee solution design involving analytics, machine learning, generative AI, computer vision, and digital twins.
• Ensure solutions are scalable, secure, and aligned with data governance and operating model requirements.
• Lead and mentor multidisciplinary teams of data engineers, data scientists, and analytics consultants.
• Support talent development, coaching, and growth of future technical and consulting leaders.
• Stay current on emerging trends in data platforms, analytics, AI, and digital transformation.

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field, strongly preferred.
• 10+ years of experience in data analytics, data engineering, and AI, with at least 5 years in a senior consulting or leadership role.
• Proven experience as a seller-doer in a consulting environment, including business development and client leadership.
• Deep experience defining and implementing enterprise data architectures and analytics platforms.
• Strong background working with public and private sector clients on complex, multi-stakeholder engagements.
• Demonstrated ability to bridge business strategy and technical execution.
• Strong proficiency in Python, SQL, and modern data platforms and engineering patterns.
• Experience with cloud data platforms such as Azure, Databricks, and Snowflake.
• Experience with machine learning and AI frameworks and analytics platforms.
• Experience with data visualization and decision-support tools such as Power BI.
• Familiarity with data governance, data management, and operating model design.

Qualifications

• Preferred Qualifications:
• Certifications in data strategy, cloud architecture, AI, or digital transformation.
• Experience implementing enterprise-scale data platforms and governance frameworks.
• Background in infrastructure, environmental, industrial, or asset-intensive sectors.