1

Geospatial Data Engineer Jobs (NOW HIRING)

Senior Geospatial Data Engineer

Mclean, VA ยท On-site

$116K - $139K/yr

The Senior Geospatial Data Engineer will build mission-critical geospatial data and analytics capabilities, using Python to process and analyze large datasets while managing geospatial information in ...

Senior Geospatial Data Engineer

Mclean, VA ยท On-site

$107K - $145K/yr

The ideal candidate is part geospatial programmer, part data librarian, and part visualization developer. You will use Python to process and analyze large geospatial datasets, manage and curate ...

Senior Geospatial Data Engineer

Mclean, VA

$107K - $145K/yr

The ideal candidate is part geospatial programmer, part data librarian, and part visualization developer. You will use Python to process and analyze large geospatial datasets, manage and curate ...

Senior Geospatial Data Engineer - Vantor

Mclean, VA ยท On-site

$117K - $141K/yr

The ideal candidate is part geospatial programmer, part data librarian, and part visualization developer. You will use Python to process and analyze large geospatial datasets, manage and curate ...

Data Layer Engineer

Tampa, FL ยท On-site

$108K - $129K/yr

The position requires working with ESRI geospatial data layers, ArcGIS Enterprise, and cloud-based geospatial services. * Engineers will implement data governance frameworks and metadata/data ...

... for engineering and construction clients nationwide. Summary Blood Hound is seeking a detail ... Collaborate with the Geospatial Systems Supervisor to improve internal data pipelines and ...

... for engineering and construction clients nationwide. Summary Blood Hound is seeking a detail ... Collaborate with the Geospatial Systems Supervisor to improve internal data pipelines and ...

next page

Showing results 1-20

Geospatial Data Engineer information

See salary details

$5

$46

$90

How much do geospatial data engineer jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for geospatial data engineer in the United States is $46.63, according to ZipRecruiter salary data. Most workers in this role earn between $35.82 and $57.69 per hour, depending on experience, location, and employer.

What is a geospatial data engineer?

A Geospatial Data Engineer is responsible for designing, developing, and managing systems that process and analyze spatial data. They work with geographic information systems (GIS), databases, and cloud platforms to handle large-scale geospatial datasets. Their role involves data pipeline development, spatial analysis, and optimizing geospatial data storage and retrieval. They collaborate with analysts, scientists, and developers to support location-based decision-making.

What are the key skills and qualifications needed to thrive as a geospatial data engineer?

To thrive as a Geospatial Data Engineer, you need solid expertise in geospatial data processing, spatial databases, GIS concepts, and programming languages like Python or SQL, typically backed by a relevant degree in geoinformatics, computer science, or a related field. Familiarity with tools such as ArcGIS, QGIS, PostGIS, and cloud platforms, as well as certifications like GISP, are highly valued. Strong analytical thinking, attention to detail, and collaborative communication enhance performance in multidisciplinary teams. These skills are vital for accurately transforming complex spatial data into actionable insights and delivering reliable solutions in geospatial projects.

What are some common challenges faced by geospatial data engineers on the job?

Geospatial Data Engineers frequently encounter challenges related to integrating large and diverse spatial datasets from multiple sources, ensuring data quality, and optimizing data for efficient querying and analysis. Managing changing project requirements and staying updated with evolving geospatial technologies are also common aspects of the role. In addition, collaborating with data scientists, analysts, and GIS specialists requires clear communication to translate technical data into actionable outputs. Navigating these challenges effectively helps engineers deliver robust geospatial solutions that support business and research goals.

What cities are hiring for Geospatial Data Engineer jobs?

Cities with the most Geospatial Data Engineer job openings:

What are the most commonly searched types of Geospatial Data Engineer jobs?

The most popular types of Geospatial Data Engineer jobs are:

What states have the most Geospatial Data Engineer jobs?

States with the most job openings for Geospatial Data Engineer jobs include:

Infographic showing various Geospatial Data Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $96,989 per year, or $46.6 per hour.

Senior Geospatial Data Engineer

Vantor

Mclean, VA โ€ข On-site

$116K - $139K/yr

Full-time

Re-posted 27 days ago


Job description

Job Summary:
Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate whatโ€™s happening now and shape whatโ€™s coming next. The Senior Geospatial Data Engineer will build mission-critical geospatial data and analytics capabilities, using Python to process and analyze large datasets while managing geospatial information in ArcGIS Portal.
Responsibilities:
โ€ข Manage, curate, publish, and maintain geospatial datasets, hosted feature layers, web maps, dashboards, and data products in ArcGIS Portal.
โ€ข Ensure mission users have access to accurate, well-organized, current, and usable geospatial information.
โ€ข Use Python, Tableau, ArcGIS, and related tools to process large datasets, automate workflows, prepare data for analysis, and build visual analytics products that reveal patterns, trends, anomalies, and operationally relevant insights.
โ€ข Partner with mission users to understand geospatial data needs, analytic questions, visualization requirements, and operational workflows.
โ€ข Identify, acquire, clean, transform, validate, curate, and publish large geospatial and tabular datasets from diverse sources.
โ€ข Develop Python scripts and tools to automate geospatial data processing, quality control, enrichment, transformation, and publication workflows.
โ€ข Manage and update ArcGIS Portal content, including hosted feature layers, map services, web maps, dashboards, data hubs, and related geospatial products.
โ€ข Build and maintain Tableau dashboards, reports, and analytic visualizations used by the data processing office and mission stakeholders.
โ€ข Apply sound cartographic design, symbology, labeling, layer management, metadata practices, and performance tuning to improve the usability of geospatial products.
โ€ข Integrate structured, unstructured, tabular, and spatial datasets into cohesive analytical and visualization environments.
โ€ข Support geospatial data library functions, including dataset organization, metadata creation, version management, quality control, discoverability, and lifecycle maintenance.
โ€ข Develop documentation, data dictionaries, standard operating procedures, user guidance, and technical recommendations that support repeatable data management and visualization workflows.
โ€ข Work independently across two office environments while collaborating with multidisciplinary teams and communicating technical concepts clearly to both technical and non-technical audiences.
Qualifications:
Required:
โ€ข Active TS/SCI security clearance with polygraph.
โ€ข Bachelorโ€™s degree in Geography, GIS, Computer Science, Data Science, Engineering, or a related technical discipline.
โ€ข 12+ years of professional experience in geospatial technology, software development, data engineering, data analysis, or a related technical field.
โ€ข Strong Python experience for geospatial data processing, automation, transformation, analysis, and workflow improvement.
โ€ข Demonstrated experience working with large geospatial datasets, including cleaning, formatting, joining, enriching, validating, and preparing data for analysis or publication.
โ€ข Hands-on experience with ArcGIS Enterprise, ArcGIS Portal, or ArcGIS Online, including publishing and maintaining hosted feature layers, web maps, dashboards, and geospatial content.
โ€ข Experience curating geospatial data holdings, including organizing datasets, maintaining metadata, improving discoverability, and ensuring data quality.
โ€ข Experience developing dashboards, reports, or analytic visualizations in Tableau or a comparable business intelligence platform.
โ€ข Understanding of geospatial data formats, projections, coordinate systems, spatial joins, geoprocessing workflows, cartographic principles, and spatial data management.
โ€ข Experience with relational databases, preferably PostgreSQL/PostGIS, for storing, querying, and managing spatial or tabular data.
โ€ข Strong analytical, problem-solving, communication, and customer engagement skills.
โ€ข Proven ability to work independently with minimal guidance while coordinating effectively across teams, offices, and mission stakeholders.
Preferred:
โ€ข Advanced Tableau experience, including dashboard development, calculated fields, filters, data preparation, publishing, and maintaining products for operational users.
โ€ข Experience with ArcGIS Pro, ArcPy, GeoPandas, Shapely, Fiona, Rasterio, GDAL, QGIS, or similar geospatial tools and libraries.
โ€ข Experience building repeatable data pipelines for geospatial data ingestion, processing, validation, and publication.
โ€ข Experience with cloud-hosted datasets, Amazon S3, ArcGIS Hub-style environments, or secure integrations between enterprise data repositories and ArcGIS Portal.
โ€ข Experience with PostgreSQL/PostGIS performance tuning, spatial indexing, and geospatial query optimization.
โ€ข Experience with Elasticsearch, Kibana, or similar search, analytics, and visualization tools.
โ€ข Familiarity with data governance, data stewardship, metadata standards, data quality, Agile practices, Jira, Confluence, DevOps principles, version control, or containerized workflows.
โ€ข Background in spatial statistics, predictive analytics, machine learning, or advanced geospatial modeling.
Company:
A spatial intelligence firm. Founded in 2025, the company is headquartered in Denver, USA, with a team of 1001-5000 employees. The company is currently Late Stage.