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Energy Forecasting Jobs in California (NOW HIRING)

Prolim Global

Platform Architect

San Francisco, CA · On-site

... and energy forecasting systems. The ideal candidate will possess deep experience in data architecture, large-scale data integration, regulatory compliance, and performance optimization within ...

Partner ESI

Energy Engineer II

Torrance, CA · On-site

$80 - $115/hr

Summary The Energy Engineer II is a mid-level technical role responsible for performing energy ... Support invoicing, forecasting, staffing coordination, and project recordkeeping * Communicate with ...

New

OpenAI

Enterprise Sales Manager, Energy

San Francisco, CA · On-site

$240K - $252K/yr

Drive disciplined pipeline generation, forecast accuracy, and operational rigor. * Guide multi ... Deep understanding of the Energy sector and how large organizations evaluate and adopt emerging ...

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All JobsEnergy Forecasting JobsEnergy Forecasting Jobs in California

Energy Forecasting information

See California salary details

$56.3K

$96.9K

$129.3K

How much do energy forecasting jobs pay per year?

As of Aug 20, 2026, the average yearly pay for energy forecasting in California is $96,875.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,500.00 and $115,500.00 per year, depending on experience, location, and employer.

What is an energy forecasting job?

An Energy Forecasting job involves analyzing historical energy consumption data, market trends, weather patterns, and other variables to predict future energy demand and supply. Professionals in this role use statistical models, machine learning, and industry expertise to assist utilities, grid operators, and energy companies in optimizing resource planning, reducing costs, and ensuring reliability. Energy forecasters play a crucial role in balancing energy generation and consumption, integrating renewable energy sources, and supporting business and policy decisions.

What are the key skills and qualifications needed to thrive in energy forecasting?

To excel in Energy Forecasting, you need strong analytical abilities, a solid background in mathematics or statistics, and preferably a degree in engineering, environmental science, or a related field. Experience with forecasting software, data analysis tools like Python, R, or MATLAB, and familiarity with energy market modeling systems are frequently required. Excellent problem-solving skills, attention to detail, and effective communication are crucial for translating complex data into actionable insights. These competencies are essential for providing accurate, reliable forecasts that support informed decision-making in energy production and consumption.

What are some of the common challenges faced by professionals in energy forecasting roles?

Professionals in energy forecasting often encounter challenges such as managing large datasets, adapting to rapidly changing market or weather conditions, and integrating new sources of energy data like renewables. Balancing historical trends with real-time information to produce reliable forecasts can require strong attention to detail and constant learning. Additionally, energy forecasters frequently collaborate with engineers, data scientists, and market analysts, so teamwork and cross-functional communication are important aspects of the role. Addressing these challenges effectively is key to providing insights that help organizations plan their operations and manage risk.

Is energy forecasting a good career?

Energy forecasting is a growing field that involves analyzing data and using modeling tools to predict energy demand and supply. It requires skills in data analysis, statistics, and knowledge of energy markets, making it a valuable and in-demand profession with opportunities for advancement. The job often involves working in a technical environment and may require relevant certifications or degrees in engineering, economics, or related fields.

What are the most commonly searched types of Energy Forecasting jobs in California?

The most popular types of Energy Forecasting jobs in California are:

What are popular job titles related to Energy Forecasting jobs in California?

For Energy Forecasting jobs in California, the most frequently searched job titles are:

What job categories do people searching Energy Forecasting jobs in California look for?

The top searched job categories for Energy Forecasting jobs in California are:

Energy Forecasting jobs near you
Infographic showing various Energy Forecasting job openings in California as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $96,875 per year, or $46.6 per hour.

Platform Architect

PROLIM Global Corporation

San Francisco, CA • On-site

Contractor

Re-posted 9 days ago

Job description

Job Title: Platform Architect - Palantir Foundry
Location: San Francisco, CA (Onsite/Hybrid as required)
Duration: 6 Months (Contract)
Job Summary
We are seeking an experienced Platform Architect with strong expertise in Palantir Foundry to design, build, and optimize scalable data platforms supporting critical grid operations, outage management, asset health monitoring, and energy forecasting systems. The ideal candidate will possess deep experience in data architecture, large-scale data integration, regulatory compliance, and performance optimization within enterprise environments.
Key Responsibilities
Data Architecture & Solution Design
  • Architect and design scalable, secure, and high-performance data platforms using Palantir Foundry.
  • Develop data architectures supporting real-time and batch processing for operational and analytical use cases.
  • Design robust workflows and pipelines to ingest data from SCADA, AMI, GIS, and ERP systems.
  • Ensure solutions align with enterprise architecture standards and business objectives.

Integration & Application Development
  • Integrate structured, semi-structured, and unstructured data sources into Palantir Foundry.
  • Develop custom applications, workflows, and services using Foundry APIs and frameworks.
  • Collaborate with data engineers and platform teams to implement best practices for data ingestion and transformation.

Data Governance & Compliance
  • Define and enforce data governance standards, access controls, and data quality frameworks.
  • Ensure compliance with NERC, FERC, and applicable state regulations.
  • Support privacy and data protection requirements, including GDPR and CCPA.

Performance Optimization & Reliability
  • Monitor, analyze, and optimize data pipelines for performance, scalability, and reliability.
  • Troubleshoot and resolve issues related to data latency, quality, and system performance.
  • Optimize platforms to handle high-volume sensor data and IoT streams.

Stakeholder Collaboration & Leadership
  • Partner with business analysts, data scientists, and operations teams to translate business requirements into technical solutions.
  • Provide technical leadership, guidance, and mentorship to junior engineers.
  • Communicate architectural decisions and technical strategies to both technical and non-technical stakeholders.

Required Qualifications
  • 8+ years of experience in data architecture, platform engineering, or solution architecture.
  • Strong hands-on expertise with Palantir Foundry, including ontology design and pipeline development.
  • Extensive experience designing real-time and batch data pipelines.
  • Proven experience integrating data from SCADA, AMI, GIS, and ERP systems.
  • Strong knowledge of data modeling concepts (Star, Snowflake, Ontology models).
  • Experience with regulatory compliance frameworks (NERC, FERC).
  • Solid understanding of data governance, security, and access control mechanisms.
  • Excellent communication and stakeholder management skills.

Preferred Qualifications
  • Experience in utilities, energy, or grid operations environments.
  • Familiarity with IoT and high-frequency sensor data platforms.
  • Prior experience mentoring or leading technical teams.
  • Exposure to cloud-based data platforms and distributed systems.

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