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Fervo Energy Tech Stack

Next-generation geothermal power development with advanced drilling and subsurface analytics

Renewables & Environment Houston, Texas 51–200 employees Founded 2017 Privately Held

Fervo Energy builds geothermal power plants engineered for 24/7 carbon-free generation. The stack reveals a heavy operations and controls focus—SCADA, DCS, Rockwell industrial controllers, and OPC UA dominate alongside subsurface modeling tools (Petrel, ArcGIS)—paired with Python-based analytics (NumPy, Pandas, SciPy) for reservoir simulation. Hiring velocity is accelerating across engineering (24 open roles) and finance/ops, with senior and manager-level positions leading the charge, signaling a shift from R&D into repeatable project deployment and cost optimization.

Tech Stack 47 technologies

Core StackCisco Fortinet Palo Alto Networks AWS Python NumPy Pandas Primavera P6 Allen-Bradley Google Analytics Canva Adobe Creative Cloud ArcGIS Workiva FloQast Quorum Azure SD-WAN SciPy Ignition ControlLogix CompactLogix Rockwell Studio 5000 Modbus TCP/IP EtherNet/IP OPC UA SCADA IEEE DCS Petrel+16 more
AdoptingAllegro

What Fervo Energy Is Building

Challenges

  • Scaling geothermal power plants
  • Simplify recurring reporting workstreams
  • Efficiency improvements across projects
  • Improving well performance
  • Cost and constructability implications
  • Aggressive deployment to meet demand
  • Optimizing cost and cycle time
  • Risk mitigation in supply chain
  • Cost-effective geothermal plants
  • Reducing utility system complexity

Active Projects

  • Design and optimization of innovative power plants
  • Develop should-cost models for completion materials
  • Design control system architectures for standardized 50 mw geothermal power blocks
  • Supplier consolidation
  • Standardization and efficiency improvements across projects
  • Total cost of ownership modeling
  • Reservoir modeling and simulation
  • Small capital improvement projects
  • Optimizing power plant cost and cycle time
  • Designing innovative power plants

Hiring Activity

Accelerating50 roles · 40 in 30d

Department

Engineering
24
Finance
7
Ops
7
Data
2
Marketing
2
Accounting
1
Construction
1
Legal
1

Seniority

Senior
20
Manager
15
Mid
8
Director
3
Lead
3

Notable leadership hires: Brand Communications Director

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About Fervo Energy

Fervo Energy develops utility-scale geothermal power plants designed to compete on cost with conventional generation while delivering round-the-clock clean power. Founded in 2017 and headquartered in Houston, the company combines geoscience innovation with modern drilling and subsurface analytics to unlock geothermal as a grid-scale resource. Current project work centers on standardizing 50 MW power block designs, reservoir modeling, cost-of-completion estimation, and supply chain consolidation—indicating a transition from prototype toward production deployment. Active pain points include scaling manufacturing, reducing drilling and construction cycle time, and managing supply chain risk across multi-site operations.

HeadquartersHouston, Texas
Company Size51–200 employees
Founded2017
Hiring MarketsUnited States

Frequently Asked Questions

What tech stack does Fervo Energy use?

Industrial controls (Rockwell ControlLogix, CompactLogix, Studio 5000), SCADA, DCS, and OPC UA for power plant operation. Subsurface work uses Petrel and ArcGIS. Financial tooling includes Workiva, FloQast, and Primavera P6. Analytics stack: Python, NumPy, Pandas, SciPy. Cloud: Azure and AWS.

Where is Fervo Energy headquartered?

Houston, Texas. The company was founded in 2017 and currently employs 51–200 people, hiring exclusively in the United States.

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How this profile is built

Fervo Energy's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.