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Full Time Geospatial Data Engineer Jobs (NOW HIRING)

Bridge Core (BCore)

Geospatial Programmer

Mclean, VA · On-site

Data Modeling & Databases - Experience modeling geospatial data and working with relational ... Data Engineering & Infrastructure - Scalable data pipeline development, performance optimization ...

Urban SDK

Data Engineer

$117K - $140K/yr

Manage large-scale geospatial and temporal datasets stored in AWS S3. * Collaborate with data ... Type: Full-time * Reports to: Director of Engineering * Salary Based on Experience * Annual Bonus

Maxar

Geospatial Data Scientist

Mclean, VA · On-site

$113K - $188K/yr

Apply geospatial data science techniques to identify patterns, trends, and mission-relevant ... S. citizenship and Active TS/SCI with required polygraph * willingness to work on-site full time ...

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How much do full time geospatial data engineer jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for full time 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 are the key skills and qualifications needed to thrive as a Full Time Geospatial Data Engineer, and why are they important?

To thrive as a Full Time Geospatial Data Engineer, you need strong expertise in GIS concepts, spatial data analysis, programming (such as Python or SQL), and a relevant degree in geography, computer science, or a related field. Proficiency with GIS software (e.g., ArcGIS, QGIS), spatial databases (like PostGIS), and cloud platforms (such as AWS or Google Cloud) is typically required, along with certifications like GISP being advantageous. Excellent problem-solving, attention to detail, and effective communication skills set top candidates apart for collaborating across teams and presenting technical findings. These skills and qualities are crucial to ensure accurate spatial data processing, reliable solutions, and effective integration of geospatial insights into business or research objectives.

How does a Full Time Geospatial Data Engineer typically collaborate with other teams within an organization?

A Full Time Geospatial Data Engineer frequently works alongside data scientists, software developers, and GIS analysts to design and implement geospatial data solutions. Collaboration often involves translating spatial data requirements into scalable data models, supporting the integration of geospatial data into larger analytics workflows, and troubleshooting data quality issues. Regular communication with cross-functional teams ensures that geospatial data products meet both technical standards and business needs. This collaborative environment not only enhances project outcomes but also provides opportunities for professional growth and exposure to diverse technologies.

What are Full Time Geospatial Data Engineers?

Full Time Geospatial Data Engineers are professionals who design, develop, and maintain systems that process and analyze geospatial data—information tied to geographic locations. They work with technologies like GIS (Geographic Information Systems), spatial databases, and programming languages to manage, transform, and visualize spatial datasets. Typically employed by organizations in fields such as environmental science, urban planning, transportation, and defense, these engineers ensure that geospatial data is accurate, accessible, and usable for decision-making. Their responsibilities often include building data pipelines, integrating various data sources, and collaborating with analysts, data scientists, and software developers.

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

AspectFull Time Geospatial Data EngineerGIS Analyst
Required CredentialsBachelor's in GIS, Geography, Computer Science; GIS certificationsBachelor's in Geography, GIS, or related field; GIS certifications
Work EnvironmentData development, database management, coding, cloud platformsMap creation, spatial analysis, data visualization, report generation
Employer & Industry UsageTech firms, government agencies, environmental companiesUrban planning, government agencies, environmental organizations
Common Search & ComparisonYesYes

The Full Time Geospatial Data Engineer primarily focuses on building and maintaining geospatial data infrastructure, coding, and managing large datasets. In contrast, a GIS Analyst emphasizes spatial analysis, map creation, and interpreting geographic data for decision-making. Both roles require similar credentials and are used across various industries, but their core responsibilities differ, with engineers handling data systems and analysts focusing on analysis and visualization.

More about Full Time Geospatial Data Engineer jobs
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 Full Time Geospatial Data Engineer jobs? States with the most job openings for Full Time Geospatial Data Engineer jobs include:
What job categories do people searching Full Time Geospatial Data Engineer jobs look for? The top searched job categories for Full Time Geospatial Data Engineer jobs are:
Full Time Geospatial Data Engineer jobs near you
Infographic showing various Full Time Geospatial Data Engineer job openings in the United States as of May 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $96,989 per year, or $46.6 per hour.
Remote Geospatial Data Engineer - Pipelines & ML

Remote Geospatial Data Engineer - Pipelines & ML

Urban SDK

Manhattan, NY • On-site, Remote

$126K - $151K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

A geospatial technology firm is seeking a skilled Data Engineer to design and maintain scalable data pipelines that support its traffic analytics applications. The role requires strong proficiency in Python and hands-on experience with Databricks and AWS S3, alongside a solid background in data engineering practices. You will collaborate with cross-functional teams to ensure efficient data workflows and optimize processing strategies for high-volume datasets.

This full-time position is available remotely or from Jacksonville, FL. #J-18808-Ljbffr

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