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Spatial Data Manager Jobs in Washington, DC (NOW HIRING)

... to manage spatial and related tabular data • Builds databases by capturing map information with coordinate digitizer • Produces computer map products depicting contents of databases, Locates ...

... spatial data types, coordinate systems, and spatial indexing * Ability to clearly communicate complex technical concepts to technical peers and non-technical project managers or customers * US ...

Understanding of geospatial data formats, spatial data standards, and data management practices. . Familiarity with cloud-based GIS environments, preferably in AWS-heavy enterprise settings.

Be a technical leader of Esri technology as well as a subject matter expert of spatial data science ... CRM, ERP, and analytics platforms * Programming and scripting experience with languages such as ...

Collaborate with GIS staff to ensure accurate spatial data integration and assetmapping. * Manage vendor relationships and coordinate with Cityworks support for issueresolution and enhancements.

SME Data Architect

Ashburn, VA · On-site

$65.25 - $83.75/hr

Seek, manage, and integrate spatial data (classified & unclassified), connecting it to mission datasets. * Design methodologies for data movement, storage, pipelines, ETL/ELT workflows, and ...

... spatial data integration and asset mapping. • Manage vendor relationships and coordinate with Cityworks support for issue resolution and enhancements. • Lead or support Cityworks-related projects ...

Showing results 41-60

Spatial Data Manager information

See Washington, DC salary details

$35.1K

$110K

$194.8K

How much do spatial data manager jobs pay per year?

As of Aug 9, 2026, the average yearly pay for spatial data manager in Washington, DC is $110,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,800.00 and $142,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a spatial data manager?

To excel as a Spatial Data Manager, you need expertise in geospatial data analysis, spatial database management, and a degree in geography, GIS, or a related field. Familiarity with GIS software (such as ArcGIS or QGIS), database systems (like PostgreSQL/PostGIS), and data standards is typically required. Strong organizational skills, attention to detail, and effective communication are vital soft skills for managing complex datasets and collaborating with stakeholders. These abilities ensure accurate data management, efficient workflows, and informed decision-making in organizations reliant on spatial information.

What are some common challenges spatial data managers face when maintaining large geospatial databases?

Spatial Data Managers often encounter challenges related to data quality, integration of multiple data sources, and ensuring data consistency across platforms. Managing large volumes of geospatial data requires robust organizational systems and regular data validation to prevent errors or duplication. Additionally, they must stay up-to-date with evolving GIS technologies and standards while coordinating with cross-functional teams like analysts, engineers, and project managers to support various mapping and spatial analysis needs.

What is the difference between Spatial Data Manager vs GIS Analyst?

AspectSpatial Data ManagerGIS Analyst
CredentialsBachelor's or higher in GIS, Geography, or related field; GIS certificationsBachelor's or higher in GIS, Geography, or related field; GIS certifications
Work EnvironmentData management teams, GIS departments, urban planning firmsMapping projects, spatial analysis teams, environmental agencies
Industry UsageOrganizations managing large spatial datasets, government agenciesAnalysis and visualization of spatial data for projects
Search & ComparisonFocuses on data management, database systems, and infrastructureFocuses on spatial analysis, mapping, and GIS software applications

The main difference is that a Spatial Data Manager oversees the organization, storage, and maintenance of spatial datasets, ensuring data quality and accessibility. In contrast, a GIS Analyst primarily conducts spatial analysis and creates maps using GIS software. Both roles require similar credentials but serve different functions within GIS projects.

What is a spatial data manager?

Spatial Data Managers are professionals responsible for organizing, maintaining, and overseeing spatial or geographic data within an organization. They ensure the accuracy, accessibility, and security of geospatial datasets used in mapping, analysis, and decision-making processes. Their role often involves using Geographic Information Systems (GIS), coordinating with other technical staff, and developing data management standards and protocols. Spatial Data Managers support various industries, including urban planning, environmental science, utilities, and transportation.
What are popular job titles related to Spatial Data Manager jobs in Washington, DC? For Spatial Data Manager jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Spatial Data Manager jobs in Washington, DC look for? The top searched job categories for Spatial Data Manager jobs in Washington, DC are:
Infographic showing various Spatial Data Manager job openings in Washington, DC as of August 2026, with employment types broken down into 82% Full Time, 16% Part Time, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $110,026 per year, or $52.9 per hour.

Senior Data Scientist (OBI Advanced Analytic Method Augmentation) - OBIQUA

CELESTAR

Reston, VA • On-site

Full-time

Medical, Dental, Life, Retirement, PTO

Re-posted 2 days ago


Job description

Celestar Corporation is seeking a Senior Data Scientist (OBI Advanced Analytic Method Augmentation) to support The Defense Intelligence Agency (DIA) under the Object Based Intelligence and Quality Assurance (OBIQUA) task order. The primary place of performance will be at DIA Facilities across the National Capital Region (NCR). If interested and meet the qualifications, we encourage you to apply for this rewarding and impactful opportunity.
ANTICIPATED AWARD: TBD
ANTICIPATED START: TBD
PERIOD OF PERFORMANCE: 1 Base Year + 4 Option Years
LOCATION: DIA Facilities across the National Capital Region (NCR)
CLEARANCE REQUIREMENT: Active TS/SCI with a Current CI Poly
About Us:
Celestar, a proud Veteran-Owned company, offers highly competitive salaries and benefits. Our comprehensive benefits package includes company-paid employee and family dental insurance, employee health insurance, life insurance, and disability coverage. Additionally, we provide a 401(k)-retirement plan with company matching, paid holidays, and personal time off.
Responsibilities:
This opportunity will support multiple DIA initiatives, including the Machine-Assisted Rapid-Repository System (MARS), Object Management Services (OMS), and Object-Based Intelligence (OBI).
• The Senior Data Scientist (OBI Advanced Analytic Method Augmentation), Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions.
• Proactively retrieves information from various sources, analyzes it for better understanding about the data set, and builds AI tools that automate certain processes.
• Duties typically include: creating various ML-based tools or processes, such as recommendation engines or automated lead scoring systems.
• Performs statistical analysis, applies data mining techniques, and builds high quality prediction systems.
• Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as Rand Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
• Should have prior experience with large data multi-INT analytics, ML, and automated predictive analytics.
• Designs, develops, and evaluates leading-edge algorithmic intelligence concepts, practices, and technologies for implementation into all-source analysis tradecraft, assessments, production, and dissemination.
• Proposes advanced statistical or mathematical techniques and methodology that may permit identification and evaluation of alternatives, assists in model formulation or experimental test design, and shares jointly in team responsibility for development of advanced analytic techniques and assessments.
• Evaluates data science, artificial intelligence, and other advanced analytic methods for risks, biases, and limitations that would distort conclusions.
• Conducts continuous independent research on methods of analysis in government, industry, and academia to keep abreast of the state of the art, keeps senior leadership apprised of the advances and applicability to programs.
• Utilizes in-depth knowledge of relevant theories, techniques, procedures and processes to investigate, prototype, and evaluate technologies to improve all-source intelligence analysis.
• Provides technical input into and participates in the development of software and computer graphics systems.
• Performs research studies to understand the process of augmenting or automating all source analytic processes using various computer models.
• Provides incremental enhancements to tools, capabilities, processes, and methods.
• Possesses in-depth knowledge and experience in using data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions.
• Writes either R or Python scripts to drive data science workflows, have experience using SQL, and managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
• Possesses prior experience with large data, spatial data, multi-INT analytics, ML, and automated predictive analytics.
• Works with ambiguous information, deconstruct key questions, leverage spatial data, exploit application programming interfaces, suggest methodologies, develop data schemas to structure observations. This requires working knowledge of coding and scripting, information science, mathematics, machine learning, visual analytic modeling tools, and relevant Standard Operating Procedures (SOPs) to create repeatable, widely applicable procedures to support all-source intelligence analysis and production.
• Creates and works in distributed analytic environments, scaling algorithms to work on increasingly large and complex datasets that are larger than RAM.
• Serves as the primary POC for data science expertise, ensuring tradecraft compliance and analytic standards as it relates to data science techniques on the contract.
• Provides advice on emerging data science methods, tools, algorithms, training, or requirements to advance DIA's analytic edge in its use of data science.
• Works with DIA vendors and the software developers to implement distributed algorithms to work on increasingly large and complex data sets.
• Review and evaluate OBI documentation submitted by advanced analytic (AA) owners to ensure compliance with tradecraft standards and adherence to best practices in AI system development and deployment.
• Assess OBI documentation for completeness, accuracy, and thoroughness, and provide detailed feedback to owners and developers.
• Provide consultation and guidance to data and AA owners, developers, and stakeholders on OBI governance and knowledge modeling, including best practices for system development, testing, and deployment.
• Assist analytic methodologists and AA owners in translating technical documentation into analytic tradecraft compliant language.
• Collaborate with stakeholders to develop, implement, and refine best practices for translating technical documentation into tradecraft compliant language
• Review and edit translated documentation to ensure accuracy, completeness, and adherence to tradecraft standards.
• Collaborate with the Computer Scientist to develop and implement testing methodologies for system validation and evaluation.
• Conduct audits to ensure compliant use of systems for approved use-cases in all source analysis.
• Develop and maintain a repository of audit findings and recommendations to facilitate knowledge sharing and best practices across the organization.
• Design and execute TEVV protocols to evaluate the performance, robustness, and fairness of systems in all source analysis contexts.
• Develop and apply statistical models and methods to analyze TEVV results and identify areas for improvement.
• Collaborate with stakeholders to develop and implement corrective actions to address TEVV findings.
• Develop and track performance metrics to evaluate the effectiveness of systems in all source analysis.
• Analyze and interpret performance metrics to identify trends, patterns, and areas for improvement.
• Collaborate with stakeholders to develop and implement data-driven decision-making processes to inform system development and improvement.
• Develop and refine methodologies for evaluating system performance, robustness, and fairness in all source analysis contexts.
• Collaborate with stakeholders to develop and implement best practices for system development, testing, and deployment.
• Supports capability development by contributing, editing, and storing code in Government owned/controlled source version control repositories.
Required qualifications/skills:
• Minimum 12 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a master's degree.
-OR-
• A minimum of 17 years of experience related to the specific labor category with at least a portion of the experience within the last 2 years with a bachelor's degree.
• Must have at least 8 years of experience in AI implementation, advanced degree in computer science, data science, or related field.
• Must have expertise in AI algorithms, model development, TEVV, and operationalization.
• Possesses a professional or graduate certificate in data science from a university, major online learning platform (all business for Data Scientists at any experience level).
• Demonstrates ability to work independently and with minimal oversight.
• Active TS/SCI Clearance within the past 5 years.
Come on board with a company that Values its Employees!
Celestar Corporation is an Equal Opportunity Employer. The Celestar Corporation prohibits discrimination, harassment, and retaliation in employment based on race; color; religion; genetic information; national origin; sex (including same-sex); sexual orientation; gender identity; pregnancy, childbirth, or related medical conditions; age; disability or handicap; citizenship status; marital status; service member/protected veteran status; or any other category protected by federal, state, or local law.