Backend Geospatial Engineer II (55626)

Who We Are 

The Center for Geospatial Solutions (CGS) is a self-sustaining nonprofit enterprise. Founded to help bridge the gap between policy and practice, our mission is to enable people and the planet to meet the pace of change by expanding access to new technologies that power more sustainable and equitable outcomes. 

We are a fully remote team of award-winning professionals with decades of applied expertise and end-to-end GIS capabilities. By embracing whole-system thinking and state-of-the-art technology, we enable partners across public, private, and nonprofit sectors to tackle complex, real-world challenges—like housing affordability, ecosystem conservation, water management, and sustainable infrastructure—with greater clarity. 

Our work liberates and connects key information, creates nuanced pictures of complex situations, and makes land, water, and social data easier to use, understand, and act on. We use tools like satellite data and artificial intelligence to deliver insights for impact. 

At CGS, we believe that technology can be a tool for positive change. We are dedicated to building a diverse team that represents the communities and systems we live and work in. If you’re excited about this role but don’t meet every listed qualification, we encourage you to apply. We value potential, curiosity, and lived experiences, and know a more inclusive team makes us a stronger organization. 

About the Lincoln Institute of Land Policy

The Lincoln Institute of Land Policy seeks to improve quality of life through the effective use, taxation, and stewardship of land. A nonprofit, private operating foundation whose origins date to 1946, the Lincoln Institute researches and recommends creative, nonpartisan approaches to land as a solution to economic, social, and environmental challenges. Through education, training, publications, and events, we integrate theory and practice to inform public policy decisions worldwide. We organize our work around three impact areas: land and water; land and fiscal systems; and land and communities. We envision a world where cities and regions prosper and benefit from coordinated land use planning and public finance; where communities thrive from efficient and equitable allocation of limited land resources; and where stewardship of land and water resources ensures a livable future. We work globally, with locations in Cambridge, Massachusetts; Washington, DC; Phoenix, Arizona; and Beijing, China.

Position Overview: 

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 (designing data models, building and maintaining APIs and processing pipelines, and integrating geospatial and cloud services), as well as owning the QA/QC layer of this work: designing validation logic, automating testing, benchmarking datasets, and baking quality-assurance practices into both projects.  

The successful candidate will combine solid backend software engineering skills with geospatial domain knowledge and a strong quality mindset. They will work closely with data scientists, AI engineers, cloud engineers, GIS professionals, project managers, and subject-matter experts to build reliable systems and ensure that CGS products are fit for their intended use.  

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