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Geospatial Data Engineer Remote Jobs (NOW HIRING)

Arva Intelligence

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Remote Base Salary Range: $95k - $130k General Position Description The Data Engineer is ... Experience working with geospatial data formats and spatial data processing * Experience supporting ...

Navtech, Inc.

URGENT NEED - Data Engineer ___ REMOTE

$117K - $140K/yr

I have an opportunity for " Data Engineer ___ REMOTE" and I am looking for a candidate who can join Immediately if you are interested, reply to me with your updated resume or if you could refer ...

SOSi

Geospatial Solutions Architect

$64.50 - $85/hr

... data into cloud-based applications. * Experience with spatial analysis, remote sensing, and geospatial AI/ML applications is required. * Possess the knowledge and capability to design and implement ...

SOSi

Geospatial Solutions Architect

$64.50 - $85/hr

... data into cloud-based applications. * Experience with spatial analysis, remote sensing, and geospatial AI/ML applications is required. * Possess the knowledge and capability to design and implement ...

NAVA Software Solutions

Data Engineer - Remote

Richmond, VA · On-site +1

$113K - $136K/yr

Data Engineer Location: 100% Remote Duration: 12 months Required Qualifications: * 7+ Years Experience in the following: Python, Java, Scala, Spark, AirFlow, Javascript/TypeScript * 3+ Years ...

NAVA Software Solutions

Data Engineer - Remote

Manhattan, NY · On-site +1

$126K - $151K/yr

Data Engineer Duration: 6-12 months Location: Remote Seeking a highly skilled and motivated Data Engineer to join a dynamic team. As a key contributor, you will be responsible for integrating into ...

NAVA Software Solutions

Data Engineer - Remote

Manhattan, NY · On-site +1

$126K - $151K/yr

Data Engineer Location: Remote Project Duration: 6-12 months Responsibilities: * Analysis, design, coding, performance tuning, and implementation of new data warehousing solutions. * Evaluation ...

Changeis

Data Engineer

$117K - $140K/yr

Data Engineer (Remote - Federal Contract Opportunity) We are seeking a Data Engineer to support U.S. Federal clients in designing, building, and maintaining scalable data solutions. This role focuses ...

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All JobsGeospatial Data Engineer Remote Jobs

Geospatial Data Engineer Remote information

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$44.5K

$129.7K

$177.5K

How much do geospatial data engineer remote jobs pay per year?

As of Jun 21, 2026, the average yearly pay for geospatial data engineer remote in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is a Geospatial Data Engineer?

A Geospatial Data Engineer is a technology professional who designs, develops, and manages systems for collecting, storing, analyzing, and visualizing geospatial (location-based) data. They work with geographic information systems (GIS), spatial databases, and cloud platforms to process large datasets from sources like satellites, drones, and sensors. In a remote setting, they collaborate with teams online to build and maintain geospatial data pipelines and support decision-making for industries such as urban planning, environmental science, and logistics.

What are the key skills and qualifications needed to thrive as a Geospatial Data Engineer in a remote role, and why are they important?

To thrive as a Geospatial Data Engineer (Remote), you need a strong background in GIS, geospatial analysis, and computer science, often supported by a related degree and experience with spatial databases. Proficiency with tools like Python, SQL, PostGIS, ArcGIS, and cloud platforms is typically required, along with relevant certifications such as GISP. Excellent problem-solving, communication, and self-management skills are essential for collaborating across distributed teams and delivering results independently. These skills ensure effective management of complex geospatial datasets, seamless integration of spatial data solutions, and success in a remote work environment.

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

AspectGeospatial Data Engineer RemoteGIS Analyst
Required CredentialsBachelor's in GIS, Geography, Computer Science; experience with GIS software and programmingBachelor's in Geography, GIS, or related field; proficiency in GIS tools
Work EnvironmentRemote, often collaborative with teams across locationsTypically office-based or hybrid; fieldwork possible
Employer & Industry UsageTech companies, government agencies, environmental firmsUrban planning, government, environmental consulting
Common Search & ComparisonOften compared for GIS and data engineering roles in remote settings

The main difference between a Geospatial Data Engineer Remote and a GIS Analyst lies in their focus and skill set. Geospatial Data Engineers primarily develop and maintain data pipelines and infrastructure, often requiring programming skills, while GIS Analysts focus on spatial data analysis and map creation. Both roles may work remotely and share similar educational backgrounds, but their daily tasks and technical expertise differ significantly.

What are the typical challenges faced by remote Geospatial Data Engineers when collaborating with distributed teams?

Remote Geospatial Data Engineers often navigate challenges such as coordinating across different time zones, ensuring data consistency, and maintaining effective communication with team members who may have varying technical backgrounds. Utilizing collaborative tools like version control systems and cloud-based platforms helps streamline workflows, but clear documentation and regular check-ins are essential to prevent misunderstandings. Building strong relationships virtually and proactively addressing technical or logistical issues can greatly enhance productivity and teamwork in a remote setting.
More about Geospatial Data Engineer Remote jobs
What cities are hiring for Geospatial Data Engineer Remote jobs? Cities with the most Geospatial Data Engineer Remote 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 Remote jobs? States with the most job openings for Geospatial Data Engineer Remote jobs include:
What job categories do people searching Geospatial Data Engineer Remote jobs look for? The top searched job categories for Geospatial Data Engineer Remote jobs are:
Geospatial Data Engineer Remote jobs near you
Infographic showing various Geospatial Data Engineer Remote job openings in the United States as of June 2026, with employment types broken down into 13% Internship, 25% As Needed, 25% Full Time, and 37% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer

Arva Intelligence

Houston, TX • On-site, Remote

$95K - $130K/yr

Other

Posted 3 days ago

Job description

Job Title:                          Data Engineer 

Department:                     Modeling & Analytics

Reports to:                       Lead Modeling Scientist

Location:                          Remote

Base Salary Range:        $95k - $130k

General Position Description

The Data Engineer is responsible for building and scaling the data and computational backbone that supports Arva's ecosystem modeling and measurement, reporting, and verification platforms. This role sits within a multidisciplinary Data Science team and focuses on designing reliable, auditable, and scalable data systems that enable biogeochemical modeling and optimization at production scale.

In this role, the Data Engineer will design and maintain production-grade data pipelines that integrate diverse datasets including field measurements, management practices, soils, and weather with process-based ecosystem models. The role plays a critical part in ensuring data quality, reproducibility, and traceability so that scientific outputs can be translated into trusted, credit-grade results with real-world impact.

Primary Job Responsibilities

Data Pipeline and Workflow Development

  • Design, implement, and maintain scalable data pipelines supporting ecosystem and biogeochemical modeling
  • Build reproducible workflows that generate standardized model inputs and manage outputs across space, time, and scenario analysis
  • Integrate heterogeneous datasets, including field data, management data, soil data, and weather data, into modeling pipelines

Cloud Infrastructure and Data Systems

  • Develop and maintain cloud-based infrastructure to support modeling pipelines and optimization workflows
  • Implement data storage solutions using relational, spatial, and object-based databases
  • Support efficient data access and processing using platforms such as PostgreSQL, PostGIS, and cloud object storage

Data Quality, Governance, and Auditability

  • Ensure data quality, versioning, traceability, and auditability to support measurement, reporting, and verification requirements
  • Implement validation and monitoring processes to ensure reliability of model inputs and outputs
  • Support transparent, repeatable workflows suitable for regulatory and credit market review

Software Engineering and Collaboration

  • Write clean, modular, and well-documented production code that supports maintainable and scalable data systems
  • Apply software engineering best practices including testing, version control, and documentation
  • Collaborate closely with Data Science and Technology teams to align data infrastructure with modeling, analytics, and production needs

Key Competencies / Requirements

  • 3+ years demonstrated experience building and maintaining data pipelines for large, complex, and heterogeneous datasets
  • Strong proficiency in Python and modern data engineering tools, with experience writing production-grade, testable code
  • Experience working with cloud platforms, with AWS strongly preferred
  • Familiarity with containerization tools such as Docker and version control systems such as GitHub
  • Experience with relational and spatial databases, including PostgreSQL and PostGIS
  • Experience working with geospatial data formats and spatial data processing
  • Experience supporting scientific or ecosystem modeling workflows preferred
  • Familiarity with workflow orchestration tools such as Airflow or Prefect preferred
  • Bachelor's or Master's degree or equivalent experience in Data Engineering, Computer Science, Environmental Informatics, or a related field

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