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Geospatial Data Analyst 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 ...

GREEN DIAMOND RESOURCE COMPANY

Geospatial Analyst

Korbel, CA · On-site

$71.05K - $106.57K/yr

You have experience with LiDAR data processing, drone-based imagery collection and processing, and ... The Geospatial Analyst supports the Sr. Geospatial Scientist in property-scale geospatial analysis ...

Dewberry

Geospatial Analyst II

Los Angeles, CA

Geospatial Analyst II Dewberry is currently seeking a Geospatial Analyst II to join our cadre of ... Our analysts provide a variety of data services for our clients including data management ...

Dewberry

Geospatial Analyst II

Sacramento, CA

Geospatial Analyst II Dewberry is currently seeking a Geospatial Analyst II to join our cadre of ... Our analysts provide a variety of data services for our clients including data management ...

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$33.6K

$81.6K

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How much do geospatial data analyst jobs pay per year?

As of Jun 1, 2026, the average yearly pay for geospatial data analyst in California is $81,558.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,700.00 and $95,700.00 per year, depending on experience, location, and employer.

What is a Geospatial Data Analyst job?

A Geospatial Data Analyst collects, processes, and interprets geographic data to identify patterns, trends, and relationships. They use Geographic Information Systems (GIS), remote sensing, and spatial analysis techniques to support decision-making in fields like urban planning, environmental management, and logistics. Their work may involve creating maps, developing models, and analyzing datasets from satellite imagery, GPS, and other sources. The role requires proficiency in GIS software, programming languages like Python or R, and strong analytical skills.

What are the key skills and qualifications needed to thrive in the Geospatial Data Analyst position, and why are they important?

To thrive as a Geospatial Data Analyst, you need a solid background in geography, spatial analysis, and data interpretation, typically supported by a degree in geography, GIS, or a related field. Experience with GIS software like ArcGIS or QGIS, database management systems, and programming languages such as Python or SQL is highly valued, along with relevant certifications like GISP. Strong analytical thinking, attention to detail, and effective communication skills are essential soft skills for conveying complex spatial data insights to diverse stakeholders. These competencies enable you to analyze and present geographic information accurately, driving impactful decision-making in sectors such as urban planning, environmental management, and logistics.

What are some typical projects or challenges a Geospatial Data Analyst might work on in this role?

Geospatial Data Analysts often work on projects such as mapping trends in urban development, optimizing transportation routes, analyzing environmental changes, or supporting emergency response planning. Common challenges include integrating large and varied datasets, ensuring data accuracy and consistency, and effectively visualizing results for non-technical audiences. On a typical day, you might collaborate with urban planners, engineers, or environmental scientists, using advanced GIS tools and spatial analytics to solve real-world problems. This role provides continuous learning opportunities as new technologies and spatial data sources emerge, making it ideal for detail-oriented and analytical professionals who enjoy tackling complex spatial questions.
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What are popular job titles related to Geospatial Data Analyst jobs in California? For Geospatial Data Analyst jobs in California, the most frequently searched job titles are:
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Geospatial Data Analyst jobs near you
Infographic showing various Geospatial Data Analyst job openings in California as of May 2026, with employment types broken down into 72% Full Time, 14% Part Time, and 14% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $81,558 per year, or $39.2 per hour.
Geospatial Data Engineer

Geospatial Data Engineer

Pano

San Francisco, CA • On-site

$111K - $144K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 12 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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