[Hiring] Backend Geospatial Engineer II @Lincoln Institute of Land Policy

Role Description

The Center for Geospatial Solutions (CGS) is seeking a Backend Geospatial Engineer II, to build and maintain the data pipelines, APIs and services for CGS’ geospatial programs. This role’s primary focus will be a complex, multi-year federal program alongside a second program focused on water reservoir system analysis and data interoperability. Across these projects and future assignments, this role carries a particular focus on evaluating and ensuring the quality, consistency, and defensibility of the datasets, remote sensing products, analytical workflows and AI-generated outputs produced.

Reporting to the Lead Cloud Engineer, this position will split their time between core backend engineering and owning the QA/QC layer of this work.

What You Will Do:

Backend Development

• Build and maintain production-quality backend services, APIs, data-access layers, workflow services, and reusable software components using Python or another appropriate language.
• Develop and optimize data models and storage solutions for raster and vector geospatial data (e.g., PostGIS, cloud-native geospatial formats).
• 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 review and architecture decisions.
• Contribute to CI/CD pipelines for infrastructure, backend applications, data workflows and analytical services.

QA/QC Specialization

• Design and implement automated tests, as well as data validation and data quality checks, as part of the program development cycle.
• Build checks for data completeness, consistency, schema conformance, spatial integrity, metadata, and analytical accuracy directly into data pipelines and services.
• Conduct accuracy assessments, error analysis, uncertainty analysis, spatial cross-validation, bias checks, and other quantitative evaluations where needed.
• 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 that could materially affect interpretation or delivery.

Standards, Reproducibility, and Process Improvement

• Collaborate with CGS colleagues to establish organization-wide QA and validation standards, templates, checklists, review gates, and documentation practices.
• Promote reproducible practices, including versioning of data, code, methods, assumptions, and outputs.
• Analyze recurring defects or process failures and recommend/implement improvements that reduce risk and rework.
• Stay current with relevant scientific, geospatial, statistical, and data-quality standards.

Communication and Delivery

• Communicate validation findings, uncertainty, limitations, and recommendations clearly 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 to deliver on scope and schedule.
• Support client and partner discussions regarding system reliability, data quality and appropriate use.

Qualifications

• Bachelor's degree or equivalent experience in computer science, software engineering, information systems, engineering, geography, environmental science, or 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 (e.g., PostGIS, GDAL, raster and vector data) and accompanying standards (e.g., OGC).
• Proficiency in Python for backend development, including building APIs and data pipelines.
• Working knowledge of geospatial data standards and architecture (e.g., OGC standards) and how they inform system design.
• Experience validating remote sensing, machine learning, deep learning, image classification, segmentation, or predictive modeling outputs.
• Experience with cloud platforms and production operations (deployment, monitoring, CI/CD) for cloud-based data and compute services, 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 appropriate interpretation of analytical results.
• Strong documentation skills and experience maintaining clear, traceable records of methods, findings, and decisions.
• Exceptional attention to detail and the ability to perform independent, objective technical review.
• Excellent written and verbal communication skills, including the ability to explain 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.

Requirements

• Familiarity with proprietary geospatial software, such as Esri’s ArcGIS Pro and ArcGIS Enterprise.
• Experience with wetland science, field delineation, hydrology, geomorphology, ecology, or environmental regulatory applications.
• Experience designing or managing field data collection, expert review, or imagery interpretation protocols.
• Experience with cloud-based data pipelines, automated testing, data contracts, or production QA systems.
• Familiarity with federal scientific standards, data-quality objectives, reproducibility requirements, or formal verification and validation practices.
• Experience authoring peer-reviewed publications, validation reports, technical methods, or audit-ready documentation.
• Experience supporting government, nonprofit, consulting, or mission-driven technical projects.

Benefits

• 3x employer contribution towards retirement matching your employee contribution up to 15%.
• Health insurance.
• Dental insurance.
• 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 insurances such as accident insurance.
• Health care flexible spending.
• Dependent care flexible spending.
• Paid time off for holidays, vacation, personal, sick, bereavement, and jury duty.
• Office closure between December 24 – Jan 1 each calendar year.
• Flexible schedule and option for a compressed 4 day workweek.
• Tuition and staff development reimbursement.
• Pet insurance.
• Employee Assistance Program.