Lead, Building Performance & Decarbonization

STV; Miami (FL); On-site; USD 102,094 - 116,679; Full time

Benefits offered by this job

Health insurance

Dental insurance

401(k) Plan

Paid Time Off

Continuing Education Program

Job summary

STV is looking for a Building Performance & Decarbonization Lead in Miami, Florida to be the primary computational strategist for sustainability advisory. This role is tailored for an advanced technical engineer adept at bridging building physics, regulatory compliance, and corporate sustainability.

The successful candidate will lead GHG inventories, oversee energy simulations, and manage sustainability software platforms to handle large environmental datasets efficiently. Candidates should possess at least 8 years of experience and a relevant engineering degree.

Qualifications

• 8+ years of advanced technical experience focused on energy simulation.
• Strong conceptual and technical understanding of modern low-carbon solutions.
• Proven experience interpreting complex energy codes and legislation.

Responsibilities

• Lead technical scoping and delivery of greenhouse gas inventories.
• Serve as an expert on energy codes and decarbonization mandates.
• Drive integration between systems to optimize efficiencies.

Skills

Energy simulation

Computational design

Building performance simulation toolsets

Understanding of low-carbon solutions

Interfacing with technical partners

Education

Bachelor’s degree in engineering or related field

Master’s degree in a related field

Tools

ClimateStudio

EnergyPlus

Grasshopper

Ladybug

Job description

STV is looking for a Building Performance & Decarbonization Lead in Miami, Florida to be the primary computational strategist for sustainability advisory. This role is tailored for an advanced technical engineer adept at bridging building physics, regulatory compliance, and corporate sustainability.

The successful candidate will lead GHG inventories, oversee energy simulations, and manage sustainability software platforms to handle large environmental datasets efficiently. Candidates should possess at least 8 years of experience and a relevant engineering degree.