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Spatial Data Jobs in Virginia (NOW HIRING)

RecruitTalent LLC.

GIS Analyst

Suffolk, VA · On-site

We are seeking a skilled GIS Analyst to manage and analyze spatial data to support decision-making processes. The ideal candidate will have at least 5 years of professional experience, a bachelor ...

RIT Solutions, Inc.

Data Engineer (763232)

Richmond, VA · On-site

$112K - $134K/yr

... spatial data to create markers on maps (lat long nearest topology of road, geo-locate between datasets, correlation etc.). • Experience with Department of Transportation Data Domains developing an ...

GRVTY

Geospatial Data Manager

Springfield, VA

$120K - $140K/yr

You will apply your expertise in GIS, data schemas, and georeferencing to organize and maintain spatial data, ensuring alignment with established metadata and extraction standards. Leveraging ...

Electrosoft

Data Architect

Arlington, VA · On-site

$73.25 - $94.25/hr

Design and maintain enterprise data architectures that support geospatial operations, spatial analytics, and mission-critical decision-making. * Develop data strategies, roadmaps, standards, and ...

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All JobsSpatial Data JobsSpatial Data Jobs in Virginia

Spatial Data information

See Virginia salary details

$44.1K

$128.6K

$176K

How much do spatial data jobs pay per year?

As of Sep 3, 2026, the average yearly pay for spatial data in Virginia is $128,604.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

What is spatial data?

Spatial data, also known as geospatial data, refers to information about the physical location and shape of objects on Earth. This data is usually stored as coordinates and topology and can represent features such as buildings, roads, rivers, or even entire countries. Spatial data is used in mapping, geographic information systems (GIS), urban planning, environmental studies, and various other fields to analyze locations, patterns, and relationships. It can be stored in formats like vector (points, lines, polygons) or raster (grids, images). Understanding spatial data is essential for making informed decisions based on geographic information.

What are some typical challenges faced by spatial data analysts when working with large geospatial datasets?

Spatial data analysts often encounter challenges related to data quality and integration when working with large geospatial datasets. Issues such as inconsistent data formats, missing metadata, and varying spatial resolutions can complicate analysis. Additionally, managing the computational load of processing and visualizing large, complex datasets may require specialized software and robust hardware. Collaborating closely with GIS specialists, IT teams, and data engineers helps to address these challenges and ensure reliable results.

What are the key skills and qualifications needed to thrive as a spatial data analyst, and why are they important?

To excel as a Spatial Data Analyst, you need a strong background in geography, GIS, data analysis, and a relevant degree such as geography, environmental science, or computer science. Proficiency in GIS software (e.g., ArcGIS, QGIS), spatial databases (like PostGIS), and programming languages such as Python or R is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills distinguish top performers in this field. These competencies are essential for accurately interpreting spatial data, generating actionable insights, and effectively sharing findings with stakeholders.

What is the difference between Spatial Data vs GIS Analyst?

AspectSpatial DataGIS Analyst
Required CredentialsGIS certifications, degrees in geography, GIS, or related fieldsGIS certifications, degrees in geography, GIS, or related fields
Work EnvironmentData collection, database management, mapping softwareData analysis, map creation, spatial problem-solving
Employer & Industry UsageUsed by GIS professionals, urban planners, environmental agenciesEmployed in government, consulting firms, environmental organizations
Search & Comparison IntentUnderstanding data types, data managementAnalyzing spatial data, creating maps, reports

Spatial Data refers to the raw geographic information used in mapping and analysis, while a GIS Analyst actively interprets, analyzes, and visualizes this data to support decision-making. Both roles require similar credentials and are integral to GIS projects, but Spatial Data is the foundational information, whereas GIS Analysts focus on applying that data to solve spatial problems.

What are popular job titles related to Spatial Data jobs in Virginia?

For Spatial Data jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Spatial Data jobs in Virginia look for?

The top searched job categories for Spatial Data jobs in Virginia are:

Spatial Data jobs near you
Infographic showing various Spatial Data job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $128,604 per year, or $61.8 per hour.

Senior Data Steward with Security Clearance

Integrity First Technologies LLC

Springfield, VA • On-site

$66.50 - $88.75/hr

Contractor

Re-posted 20 days ago

Job description

Senior Data Scientist (10+ yrs experience) - NGA Springfield, VA ​Salary Range: $155-165k Clearance Level - TS/SCI   Must haves:
• 10+ years of relevant experience. (A combination of years of experience, professional certifications, and education may be used in lieu of years of experience)
• Demonstrated understanding of GIS, data schemas, and the geo-referencing of information
• Knowledge of extraction and metadata specifications
• Knowledge of Relational Database Management System (RDBMS) architectures, best practices for data normalization, and performance tuning/optimization techniques
• Knowledge of enterprise geodatabases, such as Spatial Database Engines (SDEs)
• Knowledge of tools such as the ArcGIS Suite, ArcGIS Online, Portal, Excel, Access, and SQL for the storage, organization, and maintenance of spatial data
• Familiarity with ontology concepts as they relate to information systems, data modeling, and data relationships
• Strong collaboration skills with the ability to work effectively as a team player across technical and mission-focused teams
• Knowledge of scripting languages, such as R or Python

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