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Spatial Data Jobs in Washington, DC (NOW HIRING)

GRVTY

Data Steward -- Senior

Springfield, VA

$70.25 - $94/hr

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 ...

GRVTY

Data Steward -- Senior

Springfield, VA · On-site

$70.25 - $94/hr

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 ...

GRVTY

Data Steward -- Senior

Springfield, VA · On-site

$70.25 - $94/hr

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 ...

GeoYeti

Senior Geospatial Data Scientist

Reston, VA

Expert level understanding of spatial data storage formats such as ESRI GeoDatabases, shapefiles, GeoPackage, and text-based storage in spatial databases such as PostGIS. * Ideally an understanding ...

GeoYeti

Senior Geospatial Data Scientist

Reston, VA · On-site

Expert level understanding of spatial data storage formats such as ESRI GeoDatabases, shapefiles, GeoPackage, and text-based storage in spatial databases such as PostGIS. * Ideally an understanding ...

GeoYeti

Senior Geospatial Data Scientist

Reston, VA · On-site

Expert level understanding of spatial data storage formats such as ESRI GeoDatabases, shapefiles, GeoPackage, and text-based storage in spatial databases such as PostGIS. * Ideally an understanding ...

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All JobsSpatial Data JobsSpatial Data Jobs in Washington, DC

Spatial Data information

See Washington, DC salary details

$50.4K

$146.9K

$201K

How much do spatial data jobs pay per year?

As of Jun 15, 2026, the average yearly pay for spatial data in Washington, DC is $146,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,700.00 and $155,700.00 per year, depending on experience, location, and employer.

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 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 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 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 popular job titles related to Spatial Data jobs in Washington, DC? For Spatial Data jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Spatial Data jobs in Washington, DC look for? The top searched job categories for Spatial Data jobs in Washington, DC are:
Spatial Data jobs near you

Data Steward -- Senior

GRVTY

Springfield, VA

$70.25 - $94/hr

Other

Posted 19 days ago

Job description

What You'll Be Owning:

In this role, you will support mission-critical intelligence operations by managing, structuring, and optimizing geospatial and enterprise data to ensure accuracy, accessibility, and usability across analytic environments. 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 relational database management systems, you will design, normalize, and optimize data architectures to enhance performance and scalability, while supporting enterprise geodatabases such as Spatial Database Engines (SDEs).

What Impact You'll Have:

You will utilize tools including the ArcGIS Suite, ArcGIS Online, Portal, SQL, Oracle, Excel, and Access to store, manage, and maintain high-quality datasets that enable downstream analysis. Additionally, you will collaborate closely with analysts, engineers, and cross-functional mission partners to improve data workflows, enforce data governance best practices, and ensure that data is structured to effectively support GEOINT and multi-INT mission requirements. This role requires a proactive mindset, attention to detail, and a strong commitment to team success in a fast-paced, mission-driven environment.

What You Must Have:

  • Active TS/SCI Clearance is required with the ability to obtain a CI Poly.
  • 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

What Would Be Nice to Have:

  • Knowledge of scripting languages, such as R or Python
  • Demonstrated understanding of cartographic principles
  • Knowledge of Tableau or other data visualization tools
  • Experience supporting data governance, data stewardship, or data quality initiatives in enterprise environments
  • Certifications:
    • GEOINT Professional Certification - Fundamentals (F)
    • GEOINT Professional Certification - Geospatial Data Management (GDM)

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