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Role purpose.Technical lead responsible for integrating discipline estimates and translating detailed cost analysis into project-level cost intelligence.
Experience guideline.Typically requires 10-15 years of progressively relevant experience in the applicable professional discipline. Equivalent demonstrated capability, complexity of prior assignments, professional judgment, and leadership may be considered in level placement.
Primary Responsibilities
•Lead multidisciplinary estimate assignments and coordinate G/A/S, Electrical, Mechanical, and Site Civil inputs.
•Independently prepare and review discipline estimates and interpret evolving design information.
•Establish estimating approach, basis, coding structure, and technical work plan.
•Review estimates for completeness, consistency, scope alignment, and reasonableness.
•Lead estimate reconciliations, benchmarking, and major cost-driver analysis.
•Direct senior-level QA/QC and resolve cross-discipline scope interfaces.
•Mentor Analysts and Senior Analysts and assign technical work.
•Coordinate directly with owners, designers, PM/CM firms, and contractors.
•Develop actionable recommendations based on cost intelligence.
•Ensure consistent use of PCS data, technology, and documentation standards.
Core Competencies
Technical leadership; integration across workstreams; senior QA/QC; complex problem solving; mentoring; client facilitation; decision-oriented recommendations.
Education & Credentials
Bachelor’s degree in construction management, engineering, architecture, quantity surveying, building science, or a related field is preferred; equivalent directly relevant experience may be considered. Relevant professional credentials such as AACE, ASPE, or discipline-specific certifications are valued based on role and market requirements.
AI & Technology Expectations
Uses approved PCS technology, analytics, and AI-enabled tools responsibly; validates outputs against source information and professional judgment; protects client and company data; documents material assumptions; and escalates uncertain or unsupported outputs rather than treating AI-generated results as authoritative.