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Full Time Geospatial Data Engineer Jobs in California

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 ... In addition to base salary, full-time roles are eligible for stock options. Our benefits package ...

Vertex Sigma Software

Data Engineer

Foster City, CA · On-site

$133.50K - $160.30K/yr

AV Safety Data Engineer (Contract) The Safety Strategy & Operations team is responsible for ... Experience with geospatial data analysis. Experience with business intelligence tools (e.g., Looker ...

Vertex Sigma Software

Data Engineer

Foster City, CA · On-site

$133.50K - $160.30K/yr

AV Safety Data Engineer (Contract) The Safety Strategy Operations team is responsible for ... Experience with geospatial data analysis. Experience with business intelligence tools (e.g., Looker ...

Koniag, Inc.

Navy SEPASS Data Engineer

Monterey, CA · On-site

$185K - $195K/yr

Koniag IT Systems, LLC is seeking a Data Engineer to support enterprise-level geospatial intelligence (GEOINT) systems engineering efforts for our federal customers. The ideal candidate will bring ...

Rivian

Sr. Software Engineer, Data, Autonomy

Palo Alto, CA · On-site

$162.80K - $203.50K/yr

Implement data processing frameworks that support privacy-aware data handling, geospatial ... Full-time employee coverage is effective on their first day of employment. Part-time employee ...

Rivian

Sr. Software Engineer, Data, Autonomy

Palo Alto, CA · On-site

$162.80K - $203.50K/yr

Implement data processing frameworks that support privacy-aware data handling, geospatial ... Full-time employee coverage is effective on their first day of employment. Part-time employee ...

The Marlin Alliance

Data Engineer

San Diego, CA · On-site

$122.90K - $147.60K/yr

Required Skills and Experience: * 5 - 10 years' experience working as a business analyst, data analyst, data scientist, data engineer, database administrator, geospatial analyst, geospatial engineer ...

The Marlin Alliance

Data Engineer

San Diego, CA · On-site

$122.90K - $147.60K/yr

Required Skills and Experience: * 5 - 10 years' experience working as a business analyst, data analyst, data scientist, data engineer, database administrator, geospatial analyst, geospatial engineer ...

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Full Time Geospatial Data Engineer information

What are the key skills and qualifications needed to thrive as a Full Time Geospatial Data Engineer, and why are they important?

To thrive as a Full Time Geospatial Data Engineer, you need strong expertise in GIS concepts, spatial data analysis, programming (such as Python or SQL), and a relevant degree in geography, computer science, or a related field. Proficiency with GIS software (e.g., ArcGIS, QGIS), spatial databases (like PostGIS), and cloud platforms (such as AWS or Google Cloud) is typically required, along with certifications like GISP being advantageous. Excellent problem-solving, attention to detail, and effective communication skills set top candidates apart for collaborating across teams and presenting technical findings. These skills and qualities are crucial to ensure accurate spatial data processing, reliable solutions, and effective integration of geospatial insights into business or research objectives.

How does a Full Time Geospatial Data Engineer typically collaborate with other teams within an organization?

A Full Time Geospatial Data Engineer frequently works alongside data scientists, software developers, and GIS analysts to design and implement geospatial data solutions. Collaboration often involves translating spatial data requirements into scalable data models, supporting the integration of geospatial data into larger analytics workflows, and troubleshooting data quality issues. Regular communication with cross-functional teams ensures that geospatial data products meet both technical standards and business needs. This collaborative environment not only enhances project outcomes but also provides opportunities for professional growth and exposure to diverse technologies.

What are Full Time Geospatial Data Engineers?

Full Time Geospatial Data Engineers are professionals who design, develop, and maintain systems that process and analyze geospatial data—information tied to geographic locations. They work with technologies like GIS (Geographic Information Systems), spatial databases, and programming languages to manage, transform, and visualize spatial datasets. Typically employed by organizations in fields such as environmental science, urban planning, transportation, and defense, these engineers ensure that geospatial data is accurate, accessible, and usable for decision-making. Their responsibilities often include building data pipelines, integrating various data sources, and collaborating with analysts, data scientists, and software developers.

What is the difference between Full Time Geospatial Data Engineer vs GIS Analyst?

AspectFull Time Geospatial Data EngineerGIS Analyst
Required CredentialsBachelor's in GIS, Geography, Computer Science; GIS certificationsBachelor's in Geography, GIS, or related field; GIS certifications
Work EnvironmentData development, database management, coding, cloud platformsMap creation, spatial analysis, data visualization, report generation
Employer & Industry UsageTech firms, government agencies, environmental companiesUrban planning, government agencies, environmental organizations
Common Search & ComparisonYesYes

The Full Time Geospatial Data Engineer primarily focuses on building and maintaining geospatial data infrastructure, coding, and managing large datasets. In contrast, a GIS Analyst emphasizes spatial analysis, map creation, and interpreting geographic data for decision-making. Both roles require similar credentials and are used across various industries, but their core responsibilities differ, with engineers handling data systems and analysts focusing on analysis and visualization.

What are the most commonly searched types of Geospatial Data Engineer jobs in California? The most popular types of Geospatial Data Engineer jobs in California are:
What are popular job titles related to Full Time Geospatial Data Engineer jobs in California? For Full Time Geospatial Data Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Full Time Geospatial Data Engineer jobs in California look for? The top searched job categories for Full Time Geospatial Data Engineer jobs in California are:
Full Time Geospatial Data Engineer 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 10 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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