Lead Consultant - Data Architecture & Engineering
Role details
Job location
Tech stack
Job description
- Act as a seller-doer, originating, shaping, and closing data, analytics, and AI opportunities across priority markets
- Build trusted advisor relationships with senior client stakeholders, including executives and operational leaders
- Lead proposal development, solution shaping, and commercial structuring for complex consulting engagements
- Partner with market, sector, and account leaders to identify high-value use cases and growth opportunities
- Contribute to the evolution of GHD's Data, Analytics & AI offerings and go-to-market strategy
Client and Engagement Leadership
- Lead large, complex data and digital transformation programs from strategy through implementation
- Serve as the senior engagement lead for key clients, accountable for scope, quality, outcomes, and financial performance
- Translate business objectives into scalable data architecture, analytics, and AI solutions
- Facilitate executive workshops and working sessions to define vision, roadmap, and investment priorities
- Present insights, recommendations, and progress updates to executive and governance audiences
Technical and Solution Leadership
- Provide hands-on technical leadership in data architecture, data engineering, and analytics solution design
- Lead the creation and execution of enterprise data and AI strategies, roadmaps, and reference architectures
- Guide the design of modern data platforms across cloud and hybrid environments
- 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
Team Leadership and Capability Development
- Lead and mentor multidisciplinary teams of data engineers, data scientists, and analytics consultants
- Foster a culture of technical excellence, collaboration, and practical problem solving
- Set technical standards, review solution designs, and provide quality assurance across engagements
- Support talent development, coaching, and growth of future technical and consulting leaders
Thought Leadership and Innovation
- Stay current on emerging trends in data platforms, analytics, AI, and digital transformation
- Drive adoption of AI-enabled solutions relevant to infrastructure, environment, and asset-intensive sectors
- Contribute to internal thought leadership, client presentations, and industry forums
Requirements
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Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field strongly preferred
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10+ years of experience in data analytics, data engineering, and AI, with at least 5 years in a senior consulting or leadership role
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Proven experience as a seller-doer in a consulting environment, including business development and client leadership
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Deep experience defining and implementing enterprise data architectures and analytics platforms
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Strong background working with public and private sector clients on complex, multi-stakeholder engagements
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Demonstrated ability to bridge business strategy and technical execution
Technical Expertise
- Strong proficiency in Python, SQL, and modern data platforms and engineering patterns
- Strong 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
Leadership Skills
- Executive-level communication and presentation skills
- Strong stakeholder management and facilitation capabilities
- Ability to lead teams, influence without authority, and operate in matrixed environments
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