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Geospatial Data Engineer Remote Jobs in California

Esri

Sr. Software Development Engineer - Gen AI

Redlands, CA · On-site +1

$123K - $162K/yr

Overview Esri's Professional Services division is seeking an experienced Sr. Software Development Engineer to help advance the next generation of geospatial data quality capabilities across the ...

Esri

Sr. Generative AI Software Developer

Redlands, CA · On-site +1

$54.75 - $72.50/hr

Overview Esri's Professional Services division is seeking an experienced Sr. Software Development Engineer to help advance the next generation of geospatial data quality capabilities across the ...

REY Engineers, Inc

Extraction Technician

Folsom, CA · On-site +1

Engineers, Inc. 📍 Folsom, California | Remote and Hybrid Options | Full-Time About R.E.Y ... Interpret and translate raw geospatial data into usable engineering and survey deliverables.

The Rockridge Group

Data Engineer

Emeryville, CA · Remote

$132K - $159K/yr

TITLE: DATA ENGINEER LOCATION: 100% remote Skillsets/experience: * Engineer background * Google Applications/Analytics experience required * Google Search console experience required * Google Tag ...

Bluelight Consulting

$134K - $161K/yr

As an ETL Data Engineer, you will play a critical role in our client's expanding data engineering ... Remote

Quanata

Senior Data Engineer [Remote-US]

San Francisco, CA · Remote

$215K - $300K/yr

The role We're looking for a Senior Data Engineer to help the team deliver data science services ... We are a remote-first company for most positions so you may work from anywhere you like in the U.S ...

Lorven Technologies

Data Engineer

Los Angeles, CA · On-site +1

$123K - $148K/yr

California - Remote Duration: 6+ Months Contract The Senior Data Engineer is responsible for designing, building, and managing the data platform and tools to allow for the efficient processing and ...

Mento

Data Engineer

San Francisco, CA · Remote

$134K - $162K/yr

We are a US-based, remote-first company, backed by leading VCs and angel investors. About The Role We\'re looking for our first Data Engineer to build the data infrastructure that powers insights and ...

Crown Innovations, Inc.

AutoCAD Draftsman

Ontario, CA · On-site +1

$34.62 - $40/hr

... geospatial data, interpreting survey information, and maintaining precise engineering documentation ... remote field teams supporting airport infrastructure projects Compensation Hourly Rate Range: $34 ...

Lever Demo 2

Data Engineer

San Francisco, CA · Remote

$134K - $162K/yr

We're ready to welcome Slite's first data engineer ... This is a remote position. What's my mission ? Own the BItoolchain : pick, implement and maintain ...

JF Retail Services

Sr. Data Engineer

El Segundo, CA · On-site +1

$140K - $150K/yr

As a Senior Data Engineer at Fabletics, you will design and optimize scalable data pipelines and ... Varied for retail, fulfillment and fully remote roles. The annual basesalary range for this ...

EDO

Data Engineer

Los Angeles, CA · On-site +1

$120K - $160K/yr

... remote work days. To learn more about the work we do at EDO, please visit EDO Press . The Role As a ... What We Are Looking For * 3-6 years of experience as a Data Engineer. * Hands-on experience with ...

Lever Demo 2

Data Engineer

San Francisco, CA · Remote

$134K - $162K/yr

We're ready to welcome Slite's first data engineer ... This is a remote position. What's my mission ? Own the BItoolchain : pick, implement and maintain ...

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All JobsGeospatial Data Engineer JobsGeospatial Data Engineer Remote JobsGeospatial Data Engineer Remote Jobs in California

Geospatial Data Engineer Remote information

What is a Geospatial Data Engineer?

A Geospatial Data Engineer is a technology professional who designs, develops, and manages systems for collecting, storing, analyzing, and visualizing geospatial (location-based) data. They work with geographic information systems (GIS), spatial databases, and cloud platforms to process large datasets from sources like satellites, drones, and sensors. In a remote setting, they collaborate with teams online to build and maintain geospatial data pipelines and support decision-making for industries such as urban planning, environmental science, and logistics.

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

To thrive as a Geospatial Data Engineer (Remote), you need a strong background in GIS, geospatial analysis, and computer science, often supported by a related degree and experience with spatial databases. Proficiency with tools like Python, SQL, PostGIS, ArcGIS, and cloud platforms is typically required, along with relevant certifications such as GISP. Excellent problem-solving, communication, and self-management skills are essential for collaborating across distributed teams and delivering results independently. These skills ensure effective management of complex geospatial datasets, seamless integration of spatial data solutions, and success in a remote work environment.

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

AspectGeospatial Data Engineer RemoteGIS Analyst
Required CredentialsBachelor's in GIS, Geography, Computer Science; experience with GIS software and programmingBachelor's in Geography, GIS, or related field; proficiency in GIS tools
Work EnvironmentRemote, often collaborative with teams across locationsTypically office-based or hybrid; fieldwork possible
Employer & Industry UsageTech companies, government agencies, environmental firmsUrban planning, government, environmental consulting
Common Search & ComparisonOften compared for GIS and data engineering roles in remote settings

The main difference between a Geospatial Data Engineer Remote and a GIS Analyst lies in their focus and skill set. Geospatial Data Engineers primarily develop and maintain data pipelines and infrastructure, often requiring programming skills, while GIS Analysts focus on spatial data analysis and map creation. Both roles may work remotely and share similar educational backgrounds, but their daily tasks and technical expertise differ significantly.

What are the typical challenges faced by remote Geospatial Data Engineers when collaborating with distributed teams?

Remote Geospatial Data Engineers often navigate challenges such as coordinating across different time zones, ensuring data consistency, and maintaining effective communication with team members who may have varying technical backgrounds. Utilizing collaborative tools like version control systems and cloud-based platforms helps streamline workflows, but clear documentation and regular check-ins are essential to prevent misunderstandings. Building strong relationships virtually and proactively addressing technical or logistical issues can greatly enhance productivity and teamwork in a remote setting.
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 Geospatial Data Engineer Remote jobs in California? For Geospatial Data Engineer Remote jobs in California, the most frequently searched job titles are:
What job categories do people searching Geospatial Data Engineer Remote jobs in California look for? The top searched job categories for Geospatial Data Engineer Remote jobs in California are:
What cities in California are hiring for Geospatial Data Engineer Remote jobs? Cities in California with the most Geospatial Data Engineer Remote job openings:
Geospatial Data Engineer Remote jobs near you
Infographic showing various Geospatial Data Engineer Remote job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Real Estate Data Scientist - Remote

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA • On-site, Remote

$98K - $147K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago

Job description

The Real Estate Data Scientist is responsible for developing advanced analytical models and data-driven tools that support strategic real estate decisions across the organization. This role partners closely with Real Estate, Finance, Marketing, and Supply Chain teams to deliver predictive insights related to site selection, network optimization, sales forecasting, and market planning. This role incorporates advanced spatial modeling, geostatistics, and geospatial data engineering to evaluate trade areas, quantify market potential, and optimize network performance.
This position combines strong statistical modeling, data engineering, and business acumen to translate complex data into actionable recommendations. The Real Estate Data Scientist plays a critical role in advancing the organization's use of machine learning, automation, and predictive analytics to improve decision quality and scalability. This is a senior individual contributor role with no direct people management responsibility.
Duties and Responsibilities
  • Advanced Analytics & Predictive Modeling
    • Develop and deploy predictive models for site selection, sales forecasting, cannibalization, and market potential.
    • Build and maintain machine learning models using regression, classification, clustering, optimization, and spatial modeling techniques.
    • Apply spatial statistical methods (e.g., spatial regression, geographically weighted regression, spatial autocorrelation) to capture geographic variation in demand drivers.
    • Develop trade area and customer draw models (e.g., Huff/gravity models) to estimate market share and competitive impact.
    • Incorporate spatial features such as proximity, co-tenancy, demographics, traffic patterns, and nearby store performance into predictive models.
    • Design methodologies for forecasting store performance under various scenarios, including spatial and competitive effects.
    • Continuously monitor and improve model performance and accuracy. 
  • Data Engineering & Automation
    • Design scalable data pipelines integrating real estate, customer, demographic, sales, and geospatial datasets (parcel, census, traffic, mobility, POI data).
    • Perform geospatial data processing including geocoding, spatial joins, coordinate transformations, and spatial indexing (e.g., H3 or similar frameworks).
    • Write efficient SQL and Python workflows to automate recurring analyses, spatial feature engineering, and model refreshes.
    • Ensure data quality, consistency, and reproducibility across analytical outputs, including alignment of spatial boundaries and geographic hierarchies.
  • Real Estate Strategy & Decision Support
    • Partner with Real Estate teams to support site selection, market entry, relocations, and closures.
    • Develop drive-time and network-based trade area analyses to assess accessibility and market reach.
    • Conduct market coverage and white space analysis to identify expansion opportunities and underserved areas.
    • Build location-allocation and network optimization models to determine optimal site placement.
    • Quantify cannibalization and competitive effects using spatial overlap and proximity-based modeling.
    • Provide quantitative insights for Real Estate Committee (REC) evaluations and executive decisions.
    • Develop scoring frameworks and decision tools to prioritize opportunities.         
  • Visualization & Communication
    • Create clear, compelling visualizations and dashboards (Tableau, Power BI, or similar) to communicate insights.
    • Develop interactive geospatial visualizations including trade area maps, performance heatmaps, and market opportunity analyses.
    • Present analytical findings and recommendations to senior leadership and non-technical stakeholders.
  • Experimentation & Innovation
    • Design and execute experiments (A/B tests, quasi-experimental designs) to evaluate real estate strategies.
    • Implement geo-based testing frameworks (e.g., test vs. control markets) to measure impact of site decisions.
    • Apply causal inference methods (e.g., difference-in-differences, synthetic control) accounting for geographic spillovers.
    • Explore new data sources (e.g., mobility, foot traffic) and modeling techniques to enhance predictive capabilities.
    • Contribute to building a best-in-class real estate analytics capability.
  • Cross-Functional Collaboration
    • Work closely with GIS, Data Engineering, Finance, Marketing, and IT teams to align data and models.
    • Partner with GIS teams to ensure alignment between spatial analysis, mapping, and production data pipelines.
    • Translate business problems into analytical solutions and actionable insights.
Scope
  • Staff supervision and development:  No
  • Decision making: 
    • Develops models and analytical frameworks used in strategic decision-making
  • Travel:  Up to 10%
  • Flex Designation:  Anywhere

The anticipated salary range for this position is $98,500-$147,800 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.

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