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Geospatial Analytics Jobs in California (NOW HIRING)

Pano

Geospatial Data Engineer

San Francisco, CA · On-site

$111K - $144K/yr

Learn more at The Role As a Geospatial Data Engineer on the Geospatial Analytics team, you will design, build, and maintain the data infrastructure that powers Pano AI's geospatial analytics ...

347 Group, Inc.

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Geospatial Analyst

Santa Ana, CA · On-site

$30 - $35.40/hr

We have an immediate opportunity for a Geospatial Analyst for the Orange County area. This ideal candidate must be a self-starter who enjoys working both independently as well as with a great team.

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All JobsGeospatial Analytics JobsGeospatial Analytics Jobs in California

Geospatial Analytics information

See California salary details

$21.7K

$76.5K

$120.4K

How much do geospatial analytics jobs pay per year?

As of Jun 11, 2026, the average yearly pay for geospatial analytics in California is $76,480.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,800.00 and $79,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Geospatial Analytics professional, and why are they important?

To thrive in Geospatial Analytics, you need strong spatial analysis skills, proficiency in geographic information systems (GIS), and a background in geography, computer science, or related fields. Familiarity with tools such as ArcGIS, QGIS, remote sensing software, and programming languages like Python or R is typically required, along with relevant certifications. Analytical thinking, problem-solving, and effective communication are crucial soft skills for interpreting complex spatial data and presenting findings to diverse stakeholders. These skills and qualifications are important for delivering actionable insights that inform decision-making across industries such as urban planning, environmental management, and logistics.

What is a geospatial job?

A geospatial job involves analyzing and interpreting geographic data using tools like GIS (Geographic Information Systems), remote sensing, and spatial analysis software. Professionals in this field work on mapping, spatial data management, and geographic problem-solving to support sectors such as urban planning, environmental management, and transportation.

What is the difference between Geospatial Analytics vs GIS Analyst?

AspectGeospatial AnalyticsGIS Analyst
Required CredentialsBachelor's in Geography, GIS, or related field; proficiency in spatial analysis toolsBachelor's in Geography, GIS, or related field; GIS certifications often preferred
Work EnvironmentData analysis, modeling, and visualization in offices or remote settingsMap creation, data management, and spatial data editing in GIS software environments
Industry UsageUsed across industries like urban planning, environmental science, and transportation for data-driven decisionsPrimarily in government agencies, consulting firms, and environmental organizations for mapping and data management

While both roles involve spatial data, Geospatial Analytics focuses on analyzing and interpreting geographic data to derive insights, whereas a GIS Analyst primarily manages and creates geographic information systems and maps. Both roles often overlap but serve different core functions within the geospatial industry.

What are some common challenges faced by professionals in geospatial analytics, and how can they be addressed?

Professionals in geospatial analytics often encounter challenges such as managing large, complex datasets, ensuring data accuracy, and integrating information from diverse sources. To address these, it's important to develop strong skills in data cleaning, validation, and familiarity with various GIS and remote sensing tools. Collaboration with IT specialists and subject matter experts can also help streamline workflows and improve data integration. Staying updated on the latest industry software and best practices is key to overcoming technical hurdles and delivering actionable insights.

What does a geospatial engineer do?

A geospatial engineer analyzes and interprets geographic data using GIS (Geographic Information Systems), remote sensing, and mapping tools. They develop spatial models, create maps, and support decision-making processes in fields like urban planning, environmental management, and infrastructure development.

What does geospatial mean?

Geospatial refers to data that is related to specific locations on the Earth's surface, often used in geospatial analytics roles to analyze spatial patterns and relationships. It involves working with geographic information systems (GIS), mapping tools, and spatial data analysis techniques to support decision-making and problem-solving.

What is the meaning of geospatial data?

Geospatial data refers to information that identifies the geographic location and characteristics of natural or man-made features on the Earth's surface. In geospatial analytics, this data is used with GIS tools and spatial analysis techniques to interpret patterns, relationships, and trends related to location-based information.

What is geospatial analytics?

Geospatial analytics is the process of gathering, analyzing, and interpreting data that is associated with specific locations on the Earth. It combines geographic information systems (GIS), satellite imagery, GPS data, and other spatial data sources to uncover patterns, relationships, and trends. Geospatial analytics is widely used in fields like urban planning, environmental science, disaster response, and business intelligence to make data-driven decisions based on location-specific insights.
What are popular job titles related to Geospatial Analytics jobs in California? For Geospatial Analytics jobs in California, the most frequently searched job titles are:
What job categories do people searching Geospatial Analytics jobs in California look for? The top searched job categories for Geospatial Analytics jobs in California are:
What cities in California are hiring for Geospatial Analytics jobs? Cities in California with the most Geospatial Analytics job openings:
Geospatial Analytics jobs near you
Geospatial Data Engineer

Geospatial Data Engineer

Pano

San Francisco, CA • On-site

$111K - $144K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago

Job description

Help us tackle the growing wildfire crisis with the latest advancements in AI and IoT
Who we are
The problem: Every minute matters in fire response. As climate change amplifies the intensity of wildfires-with longer fire seasons, dryer fuels, and faster winds-new ignitions spread faster and put more communities at risk. Today, most wildfires are detected by bystanders and reported via 911, meaning it can take hours to detect a fire, verify its exact location and size, and dispatch first responders. Fire authorities need a faster way to detect, confirm, and pinpoint fires so that they can quickly respond-preventing small flare-ups from becoming devastating infernos.
About Pano: We are a 175+ person growth-stage hybrid-remote start-up, headquartered in San Francisco. We are the leader in early wildfire detection and intelligence, helping fire professionals respond to fires faster and more safely-with the right equipment, timely information, and enhanced coordination-so that they can stop a new ignition before it grows. Pano AI combines advanced hardware, software, and artificial intelligence into an easy-to-use, web-based platform. Leveraging a network of ultra-high-definition, 360-degree cameras atop high vantage points, as well as satellite and other data feeds, Pano AI produces a real-time picture of threats in a geographic region and delivers immediate, actionable intelligence.
Pano AI has been recognized by Fast Company as one of the Top 10 Most Innovative AI Companies in 2023, and as one of the Top 50 Most Innovative Companies of 2026-ranking #1 in the Sustainability category. The company was also named to TIME's list of the 100 Most Influential Companies of 2025 and identified by MIT Technology Review as one of the top 15 climate tech companies to watch in 2024. Pano AI has been featured in leading publications, including The Wall Street Journal, Bloomberg, and CNBC.
The company serves dozens of government and enterprise customers across 16 U.S. states, five Australian states, and British Columbia, Canada, and currently monitors more than 50 million acres of land worldwide. It has raised $89 million in venture capital from investors including Giant Ventures, Liberty Mutual Ventures, Tokio Marine Future Fund, Congruent Ventures, Initialized Capital, Salesforce Ventures, and T-Mobile Ventures. Learn more at https://www.pano.ai/.
The Role
As a Geospatial Data Engineer on the Geospatial Analytics team, you will design, build, and maintain the data infrastructure that powers Pano AI's geospatial analytics workflows-from ingestion pipelines and spatial databases to automated processing systems and internal tooling. This role works closely with geospatial data analysts, data scientists, and cross-functional partners in Sales, Operations, Product, and Engineering to ensure that spatial data is reliable, scalable, and readily accessible. An ideal candidate brings 2-4 years of experience in data or software engineering, solid command of Python and SQL, and hands-on familiarity with geospatial data formats and spatial databases. You will contribute to the full data lifecycle, writing clean and well-tested code, participating in code reviews, and helping establish engineering standards on a growing team.
What you'll do
  • Design, build, and maintain scalable data pipelines that ingest, transform, and load geospatial datasets to support efficient and scalable geospatial analytics
  • Develop and optimize PostGIS and PostgreSQL database schemas to support geospatial analytics, viewshed computations, and site selection workflows
  • Write and maintain Python-based automation scripts and geospatial processing tools, following software engineering best practices including code reviews, pull requests, and version control with Git/GitHub
  • Collaborate with geospatial data analysts and scientists to understand data requirements and translate them into reliable, well-documented engineering solutions
  • Monitor and maintain data quality, pipeline reliability, and system performance for production geospatial data products
  • Support integration of geospatial data infrastructure with internal dashboards, APIs, and product engineering systems
  • Support analytics workflows as needed
  • Contribute to special projects and cross-functional initiatives as the team's data infrastructure needs evolve

What you'll bring
  • Bachelor's degree in Computer Science, Engineering, Geography, Statistics, Math, or a related field
  • 2-4 years of experience in data engineering, software engineering, or a closely related role
  • Proficiency in Python, including experience writing modular, tested, and maintainable code using geospatial Python libraries such as GeoPandas, Shapely, Rasterio, or GDAL
  • Solid SQL skills and hands-on experience with PostgreSQL and PostGIS for querying and managing spatial data
  • Fluency with Git/GitHub workflows, including branching strategies, pull requests, and code reviews
  • Working knowledge of geospatial data formats (GeoJSON, GeoTIFF, Shapefile, etc.) and coordinate reference systems
  • Experience building or maintaining ETL or data pipeline workflows in a production environment
  • Strong communication skills and ability to work collaboratively across technical and non-technical stakeholders
  • Experience with ArcGIS Pro or QGIS highly preferred

Nice to have
  • Experience with cloud-based geospatial platforms or data warehouses (e.g., BigQuery, Snowflake, AWS, or GCP)
  • Experience with Salesforce integrations
  • Experience with ArcGIS Online and ArcGIS Enterprise
  • Experience with workflow orchestration tools such as Temporal, Airflow, Prefect, or similar

Final compensation for full-time employees is determined by a variety of factors, including job-related qualifications, education, experience, skills, knowledge, and geographic location. In addition to base salary, full-time roles are eligible for stock options. Our benefits package also includes comprehensive medical, dental, and vision coverage, a matching 401(k) plan, and flexible paid time off.

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