Backend Geospatial Engineer II

Lincoln Institute of Land Policy

. Build and maintain production-quality backend services, APIs, data-access layers, workflow services, and reusable software components .

Posted 10/8/2026contractRemote • United StatesMid-LevelSenior💰 $80,000 - $96,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in backend software development with a focus on geospatial data, including proficiency in Python and experience with geospatial APIs and data architecture. Strong capabilities in data validation, quality assurance, and effective communication of technical findings to diverse audiences.

Highest-signal resume keywords

Backend Software DevelopmentGeospatial Data ArchitecturePython ProgrammingData Validation and Quality AssuranceCI/CD Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend Software DevelopmentGeospatial Data ArchitecturePython ProgrammingData ValidationSpatial StatisticsETL/ELT Pipeline DevelopmentAPI DevelopmentAutomated TestingAccuracy AssessmentsData Quality Checks

Soft Skills

Attention to DetailWritten CommunicationVerbal CommunicationIndependent ReviewCollaboration

Tools & Technologies

AWSGCPAzurePostGISGDALArcGIS ProArcGIS EnterpriseGitGitHubCI/CD Tools

Industry Keywords

Geospatial DataRemote SensingEnvironmental ScienceData Interoperability StandardsFederal Scientific StandardsReproducibility RequirementsValidation PracticesField Data CollectionTechnical DocumentationPeer-Reviewed Publications

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformPostGISPythonRemote Sensing

About the role

Key responsibilities & impact

Build and maintain production-quality backend services, APIs, data-access layers, workflow services, and reusable software components
Develop and optimize data models and storage solutions for raster and vector geospatial data
Build and maintain ETL/ELT pipelines that ingest, process, and transform geospatial and remote sensing data at scale
Integrate cloud services for data storage, compute, and orchestration of geospatial workflows
Write clean, maintainable, well-tested code and participate in code reviews and architecture decisions
Contribute to CI/CD pipelines for infrastructure, backend applications, data workflows, and analytical services
Design and implement automated tests, data validation, and data-quality checks
Build checks for data completeness, consistency, schema conformance, spatial integrity, metadata, and analytical accuracy
Conduct accuracy assessments, error analysis, uncertainty analysis, spatial cross-validation, bias checks, and other quantitative evaluations
Create, curate, and maintain benchmark and reference datasets for automated validation and regression testing
Document validation methods, test results, and acceptance decisions
Identify data gaps, methodological weaknesses, and limitations affecting interpretation or delivery
Establish QA and validation standards, templates, checklists, review gates, and documentation practices
Promote reproducible practices through versioning of data, code, methods, assumptions, and outputs
Analyze recurring defects or process failures and implement improvements to reduce risk and rework
Communicate validation findings, uncertainty, limitations, and recommendations to technical and non-technical audiences
Contribute technical and QA documentation to reports, client deliverables, proposals, presentations, and publications
Coordinate development and QA activities with project managers and technical leads
Support client and partner discussions regarding system reliability, data quality, and appropriate use

Requirements

What you’ll need

Bachelor's degree or equivalent experience in computer science, software engineering, information systems, engineering, geography, environmental science, or a related technical field
3+ years of professional backend software development experience, including meaningful work in geospatial data
Experience working with geospatial APIs and data interoperability standards such as pygeoapi
Knowledge of geospatial data architecture, including PostGIS, GDAL, raster and vector data, and OGC standards
Proficiency in Python for backend development, including building APIs and data pipelines
Working knowledge of geospatial data standards and architecture
Experience validating remote sensing, machine learning, deep learning, image classification, segmentation, or predictive modeling outputs
Experience with cloud platforms and production operations, including deployment, monitoring, and CI/CD, such as AWS, GCP, or Azure
Familiarity with CI/CD practices
Experience with Git/GitHub or comparable version-control workflows
Experience designing and conducting accuracy assessments, validation studies, sampling strategies, or quantitative quality evaluations
Strong knowledge of spatial statistics, uncertainty, bias, error metrics, and interpretation of analytical results
Strong documentation skills and experience maintaining clear, traceable records of methods, findings, and decisions
Exceptional attention to detail and ability to perform independent, objective technical review
Excellent written and verbal communication skills, including explaining technical limitations and risk to varied audiences
U.S. Citizen, or legally authorized to work in the U.S. with no need for future sponsorship
Helpful: familiarity with ArcGIS Pro and ArcGIS Enterprise
Helpful: experience with wetland science, field delineation, hydrology, geomorphology, ecology, or environmental regulatory applications
Helpful: experience designing or managing field data collection, expert review, or imagery interpretation protocols
Helpful: experience with cloud-based data pipelines, automated testing, data contracts, or production QA systems
Helpful: familiarity with federal scientific standards, data-quality objectives, reproducibility requirements, or formal verification and validation practices
Helpful: experience authoring peer-reviewed publications, validation reports, technical methods, or audit-ready documentation
Helpful: experience supporting government, nonprofit, consulting, or mission-driven technical projects

Benefits

Comp & perks

3x employer contribution towards retirement matching employee contribution up to 15%
Health insurance, with the Institute paying 90–95% of medical plan costs
Dental insurance, with all dental plan costs paid by the Institute
Vision insurance
100% reimbursement of the health care deductible through a health reimbursement account
Short-term disability coverage
Long-term disability coverage
Paid parental leave
Voluntary accident insurance
Health care flexible spending account
Dependent care flexible spending account
Paid holidays, vacation, personal, sick, bereavement, and jury duty leave
Office closure between December 24 and January 1 each calendar year
Flexible schedule
Option for a compressed four-day workweek
Tuition and staff development reimbursement
Pet insurance
Employee Assistance Program