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Geospatial Data Engineer Jobs in Houston, TX (NOW HIRING)

Arva Intelligence

Data Engineer

Houston, TX · On-site

$95K - $130K/yr

Data Engineer Department : Modeling & Analytics Reports to : Lead Modeling Scientist Location ... Experience working with geospatial data formats and spatial data processing * Experience supporting ...

Arva Intelligence

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Data Engineer Department : Modeling & Analytics Reports to : Lead Modeling Scientist Location ... Experience working with geospatial data formats and spatial data processing * Experience supporting ...

SynMax

Senior Full-Stack Engineer

Houston, TX · Remote

Partnering with other developers on large-scale projects, you will leverage your deep technical ... Ensure vast quantities of geospatial and tabular data are visually explorable in a reproducible ...

SynMax

Senior Full-Stack Engineer

Houston, TX · On-site +1

Partnering with other developers on large-scale projects, you will leverage your deep technical ... Ensure vast quantities of geospatial and tabular data are visually explorable in a reproducible ...

BaRupOn LLC

Surveying and Mapping Engineer

Liberty, TX · On-site

$48K - $70K/yr

Prepare and maintain site maps, plats, alignments, and geospatial data * Support civil, structural, and utility design with accurate survey inputs * Coordinate survey activities with engineering ...

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Geospatial Data Engineer information

See Houston, TX salary details

$5

$44

$86

How much do geospatial data engineer jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for geospatial data engineer in Houston, TX is $44.53, according to ZipRecruiter salary data. Most workers in this role earn between $34.18 and $55.10 per hour, depending on experience, location, and employer.

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 are the key skills and qualifications needed to thrive in the Geospatial Data Engineer position, and why are they important?

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 is a Geospatial Data Engineer job?

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 most commonly searched types of Geospatial Data Engineer jobs in Houston, TX? The most popular types of Geospatial Data Engineer jobs in Houston, TX are:
What are popular job titles related to Geospatial Data Engineer jobs in Houston, TX? For Geospatial Data Engineer jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Geospatial Data Engineer jobs in Houston, TX look for? The top searched job categories for Geospatial Data Engineer jobs in Houston, TX are:
Geospatial Data Engineer jobs near you
Infographic showing various Geospatial Data Engineer job openings in Houston, TX as of July 2026, with employment types broken down into 100% Full Time. Highlights an 77% In-person, and 23% Remote job distribution, with an average salary of $92,622 per year, or $44.5 per hour.

Data Engineer

Arva Intelligence

Houston, TX • On-site

$95K - $130K/yr

Full-time

Posted 28 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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