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Entry Level Geospatial Data Engineer Jobs (NOW HIRING)

GRVTY

Geospatial Data Scientist

Mclean, VA

There are recurring opportunities on this team for Analytic / BigData Software Developers, Full ... THE ROLE The Geospatial Data Scientist is responsible for gathering project requirements from the ...

Lynker Corporation

Geospatial Data Analyst

Charleston, SC · On-site

$78K - $92K/yr

Work with office IT, Data Engineers (DBAs), and application developers in deploying new data ... Experience processing geospatial data in the Cloud About Lynker Lynker is a growing, employee owned ...

GRVTY

Geospatial Data Scientist

Mclean, VA

There are recurring opportunities on this team for Analytic / BigData Software Developers, Full ... THE ROLE The Geospatial Data Scientist is responsible for gathering project requirements from the ...

GRVTY

Geospatial Data Scientist

Mclean, VA · On-site

There are recurring opportunities on this team for Analytic / BigData Software Developers, Full ... THE ROLE The Geospatial Data Scientist is responsible for gathering project requirements from the ...

Chenega MIOS

Jr. Geospatial Engineer

Vienna, VA

Support data automation, migration, and database development efforts * Coordinate tasks with ... From entry-level employees to senior leaders, we believe theres always room to learn. We offer ...

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How much do entry level geospatial data engineer jobs pay per hour?

As of May 31, 2026, the average hourly pay for entry level 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 an Entry Level Geospatial Data Engineer, and why are they important?

To thrive as an Entry Level Geospatial Data Engineer, a solid understanding of GIS concepts, spatial data analysis, and a relevant degree in geography, computer science, or a related field is essential. Familiarity with tools like ArcGIS, QGIS, Python, and SQL, as well as experience with geospatial databases, is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help individuals excel in collaborating with teams and interpreting complex data. These skills ensure accurate geospatial solutions and support critical decision-making in industries like urban planning, environmental management, and logistics.

What are some common challenges faced by entry level geospatial data engineers when working with large spatial datasets?

Entry level geospatial data engineers often encounter challenges related to the size and complexity of spatial datasets, such as slow processing times, data quality issues, and difficulties with data integration from various sources. Learning to use specialized tools like GIS software and spatial databases efficiently is crucial for handling these challenges. Collaborating with more experienced engineers and data scientists can help new hires develop best practices for data cleaning, transformation, and visualization, which are key skills in this role.

What are entry level geospatial data engineers?

Entry level geospatial data engineers are professionals who work with geographic information systems (GIS) and spatial data to collect, process, and analyze location-based information. They use programming, data management tools, and mapping software to support projects in fields such as urban planning, environmental science, and logistics. At the entry level, these engineers assist in database maintenance, data cleaning, and creating visualizations while learning industry standards and best practices.

What is the difference between Entry Level Geospatial Data Engineer vs GIS Analyst?

AspectEntry Level Geospatial Data EngineerGIS Analyst
Required CredentialsBachelor's in GIS, Geography, Computer Science; some certificationsBachelor's in GIS, Geography; certifications like GISP are common
Work EnvironmentData processing, database management, scripting, software developmentMap creation, spatial analysis, data visualization, report generation
Employer & Industry UsageTech firms, government agencies, environmental companiesUrban planning, government agencies, consulting firms
Common Search & ComparisonYesYes

Entry Level Geospatial Data Engineers focus on building and managing spatial data systems, often involving programming and database skills. GIS Analysts primarily analyze and visualize spatial data to support decision-making. While both roles require GIS knowledge, Data Engineers emphasize data infrastructure, whereas Analysts focus on spatial analysis and reporting.

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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 Entry Level Geospatial Data Engineer jobs? States with the most job openings for Entry Level Geospatial Data Engineer jobs include:
What job categories do people searching Entry Level Geospatial Data Engineer jobs look for? The top searched job categories for Entry Level Geospatial Data Engineer jobs are:
Entry Level Geospatial Data Engineer jobs near you

Geospatial Data Scientist

GRVTY

Mclean, VA

Other

Posted 18 days ago

Job description

What Impact You'll Have:

Our team integrates hundreds of data sources into a Geospatial Data Analysis platform used throughout the Intelligence Community. Their tool and dataset is widely-recognized as the leading platform for geospatial analysis, touching nearly every type of mission. Top government officials use analysis from this platform to make daily decisions that have global impact. The platform is constructed of 3rd party tools and custom applications, and new data sources are constantly being added. The customer is excellent to work with, and there is a healthy mix of customer-driven requirements and team-driven ideas / innovation: engineers typically have freedom in choosing how to do things and which technologies to utilize. Customer leadership also helps drive innovation and has created a close, collaborative idea exchange between staffers and contractors. Our Team Lead has said "this is simply the best group of people I've worked with". Despite this platform being widely used, there is a huge amount of brand new work adding new capabilities and data sources, as well as migrating more and more of the subsystems to AWS. There are recurring opportunities on this team for Analytic / BigData Software Developers, Full Stack Software Engineers, Web Application Developers, Java Developers, JavaScript Developers, Python Developers, Geospatial (GIS) Developers, ETL Developers, Data Scientists, Data Engineers, Data Analysts, AWS Engineers, DevOps Engineers, Cloud Migration Experts, and Geospatial Systems Engineers. Work on this program takes place in the McLean, VA area (we cannot support remote work) and requires a TS/SCI + Poly clearance (acceptable by this customer). THE ROLE The Geospatial Data Scientist is responsible for gathering project requirements from the customer and implementing data-driven solutions. They can expect to use Python, PostgreSQL, and AWS tools on a daily basis to establish automated ETL (Extract, Transform, Load) pipelines, implement geospatially focused analytics, and create data visualizations to be shared with a wide range of audiences. In addition to these core functions, the Data Scientist helps to ensure that the project's data architecture is scalable, maintains high data quality/integrity, and is streamlined to maximize performance.

What You'll Be Owning:

GRVTY is seeking a Geospatial Data Scientist with a TS/SCI + Poly clearance (applicable to this customer) to join one of our top projects in Mclean, VA

What You Must Have:

  • Active TS/SCI with Polygraph Clearance
  • Minimum 3 years of experience with a Bachelor's degree or 1 year of experience with a Master's degree
  • Python experience to automate data transformation and analysis of geospatial datasets
  • Experience working with PostgreSQL to extract data from RDBMS
  • Experience with AWS tools Linux experience
  • Experience with API Connections
  • Comfortable working with all types of geospatial datasets in thick client applications (e.g. ArcGIS) 

What Would Be Nice to Have:

  • Experience working with R, Tableau
  • Experience working with NiFi

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