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Global Chief Estimating Lead Director– Data Center Fit-Out
OracleUnited States, United Statesfull_timeVerifiedPosted 9 Jan 2026
💰 $291,800/yr($139,400/yr – $291,800/yr)
About the role
Lead the global estimating function for a large-scale, leased data center build program, responsible for end‑to‑end estimating governance, standardization, and execution. Own development of funding and stage-gate estimates, “should-cost” change-order assessments, and continuous benchmarking. Establish and maintain the global Cost Breakdown Structure (CBS) and a centralized cost database, integrating with program controls, procurement, finance, and regional delivery teams to ensure cost predictability, transparency, and compliance.
Key Responsibilities
- Estimating Leadership and Governance
- Define and enforce global estimating standards, procedures, and QA/QC aligned to AACE Class 5–Class 1 maturity and program stage gates.
- Build and lead a high-performing estimating team (regional leads, discipline estimators, data analysts) with clear roles, SLAs, and succession plans.
- Chair the Estimate Review Board; provide independent cost assurance for major funding decisions.
- Oversee development of funding estimates
- Produce CAPEX fit‑out estimates for funding requests at each gate, aligned to scope, design maturity, and risk profile.
- Structure estimates to distinguish co-lo shell vs. tenant fit‑out, TI allowances, and capitalizable vs. expensed items (GAAP/IFRS).
- Apply escalation, FX, location factors, productivity, market capacity, and procurement strategy assumptions with traceable basis-of-estimate.
- Develop should‑cost models and unit‑rate libraries to evaluate vendor proposals and change orders for reasonableness.
- Support negotiations with LV and other contractors; provide claim analysis and cost entitlement assessments.
- Maintain a variance log with drivers (scope, rates, quantities, productivity, market) and recommended mitigations.
- Cost Breakdown Structure (CBS) and WBS Alignment
- Establish a standardized global CBS tailored to data center fit‑outs (e.g., civil, structural, architectural, mechanical, electrical, controls/BMS/SCADA, fire protection, racks/containment, network/telecom, security, commissioning, indirects, GC fee, contingency, owner costs, co-lointerfaces).
- Build and govern a centralized cost database with location factors, currency, FX history, escalation indices, and vendor rate cards.
- Implement data quality standards, coding, and metadata to enable parametric and benchmark estimating across regions and facility tiers.
- Publish quarterly market intelligence and cost indices; refresh benchmarks after each project closeout (lessons learned).
- Quantify risk and uncertainty; develop deterministic and probabilistic contingencies aligned to estimate classes.
- Procurement and Market Interface
- Support contracting strategies for long‑lead equipment (switchgear, generators, UPS, CRAH/CRAC, transformers) and multi‑region framework agreements.
- Prepare should‑costs for alternates and value engineering, ensuring TCO and reliability requirements are met.
- Reporting and Stakeholder Management
- Provide clear basis-of-estimate narratives, assumptions, exclusions, and confidence ranges.
- Interface with Design, Delivery, Commissioning, Operations, Finance, and Co-lo teams to maintain scope-cost alignment.
- Implement enterprise tools for estimating, cost control, and reporting; integrate with ERP, commitments, and change control.
Core Deliverables
- Global estimating standards and procedures (including class definitions, BOE templates, QA checklists)
- Master CBS and coding dictionary mapped to WBS, ERP, and reporting hierarchies
- Centralized cost database and benchmark library with regional indices and escalation curves
- Should‑cost models and unit‑rate libraries for key trades and major equipment
- Stage-gate estimates with confidence intervals and risk-adjusted contingencies
- Independent cost reviews for large funding requests and major change events
- Quarterly cost intelligence reports and annual update to location factors
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