The Geospatial Analyst III is a senior analyst responsible for leading complex data processing workflows, ensuring the quality and completeness of all project deliverables, and providing technical guidance to less experienced analysts. This role takes full ownership of LiDAR processing, field imagery QA, GIS data management, and deliverable finalization across assigned projects, operating with minimal supervision. The Geospatial Analyst III actively supports QA/QC standards across the team, drives processing efficiency, mentors junior analysts, and contributes to the continuous improvement of the data pipeline that connects field operations to client-ready outputs.
Essential Duties and Responsibilities
Data Ingestion and Pipeline Oversight
- Oversee the receipt, verification, and organization of incoming field data from Survey Technicians and UAS Pilots, ensuring packages are complete, correctly structured, and ready for processing before work begins.
- Identify systemic submission gaps, naming convention issues, or recurring data quality problems and communicate actionable recommendations to the Geospatial Solutions Supervisor.
- Manage data organization, storage, and tracking across multiple concurrent projects with precision and consistency.
LiDAR Data Processing
- Execute advanced LiDAR point cloud processing and conversion into LAS file formats, maintaining the highest standards of accuracy and quality across all deliverables.
- Optimize processing workflows to improve efficiency and reduce project turnaround times.
- Perform thorough QA on processed LiDAR outputs before they advance to reporting or delivery stages.
Field Imagery Quality Assurance
- Conduct comprehensive quality control of all field photography from Survey Technicians and UAS Pilots, verifying completeness, clarity, and compliance with company and client standards.
- Identify and resolve imagery quality issues, coordinating with field teams and junior analysts to ensure corrective action is taken.
- Set and reinforce photo QA standards across the team.
Deliverable Preparation and Finalization
- Prepare, compile, and finalize detailed condition assessment reports by synthesizing LiDAR data, field imagery, pole and conductor data, and other field inputs into polished, client-ready deliverable formats.
- Manage thermal imagery datasets and ensure seamless integration into analysis and reporting workflows.
- Develop and finalize GPR reports with comprehensive data analysis supporting engineering and project decision-making.
- Review and approve deliverables prepared by junior analysts, ensuring all outputs meet project specifications and client standards before submission.
GIS Data Management
- Maintain and update GIS datasets across active projects, ensuring high data integrity and usability for field and office applications.
- Lead GIS data integration efforts, applying advanced proficiency across platforms and data formats.
- Identify opportunities to improve GIS data workflows and recommend enhancements to the Geospatial Solutions Supervisor.
Quality Assurance and Process Improvement
- Apply and enforce QA/QC standards consistently across the full processing workflow, identifying issues at each stage before they affect downstream deliverables.
- Review processed data and deliverables prepared by junior analysts, providing constructive technical feedback.
- Identify recurring quality issues, inefficiencies, or workflow gaps and bring recommendations for improvement to the Geospatial Solutions Supervisor.
- Contribute to the development and refinement of processing standards, templates, and documentation used by the team.
Mentorship and Team Support
- Provide technical mentoring and guidance to Geospatial Analyst I and II team members, helping them develop processing skills and apply company and client standards correctly.
- Serve as the primary technical resource for processing questions related to LiDAR, GIS, imagery QA, and deliverable preparation.
- Support a consistent, high-quality output environment by modeling thoroughness and professional accountability.
Coordination and Communication
- Coordinate with field teams regarding data submissions, quality issues, and project-specific requirements.
- Communicate deliverable status, processing timelines, and quality concerns to the Geospatial Solutions Supervisor clearly and proactively.
- Support data integration initiatives and contribute to innovation efforts that advance the department's technical capabilities.
Additional Responsibilities
- Perform all duties as directed by the Geospatial Solutions Supervisor, contributing broadly to project quality and departmental goals.
Qualifications
- Associate degree in Geomatics, Surveying, Geography, GIS, or a related field required.
- Minimum 3-4 years of professional experience in geospatial data processing, LiDAR analysis, GIS management, or a directly related field.
- Demonstrated expertise in LiDAR data processing workflows and LAS file formats.
- Proven experience performing and overseeing field imagery QA and managing complex, multi-source data pipelines.
- Advanced proficiency with GIS applications and geospatial data management platforms.
- Proficiency with Microsoft Office Suite, Adobe Pro, and other relevant software.
- Technically precise with a strong record of producing accurate, complete deliverables.
- Strong communicator who can identify and elevate issues clearly and recommend practical solutions.
Preferred Qualifications
- Bachelor's degree in a related field preferred.
- Significant additional technical training or professional development in geospatial processing, remote sensing, or LiDAR analysis.
- Experience supporting or conducting QA/QC reviews in a production data environment.
- Extensive expertise in LiDAR data processing, including advanced LAS file handling and point cloud analysis.
- Strong capability in field imagery quality assessment and deliverable preparation.
- Experience with data integration tools, platforms, and API-based workflows.
- Self-directed and capable of managing complex processing workloads across multiple projects with minimal supervision.
- Willing and able to mentor less experienced analysts constructively and professionally.
- Demonstrated ability to share technical knowledge and guide others in developing processing skills and applying quality standards effectively.