ZenaTech, Inc.
QA LiDAR Processing Engineer
Skills
4 days ago
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Important information
Contract type:
Permanent
Salary:
CA$65,000 – CA$80,000 / year
Location:
Toronto, ON, Canada
Work mode:
Onsite
Published on:
16 October 2026
What they need
About Us:
ZenaTech (Nasdaq: ZENA | FSE: 49Q) is a technology company specializing in AI drones, Drone-as-a-Service (DaaS), enterprise SaaS, and quantum computing solutions for mission-critical business applications. Since 2017, the company has leveraged its software development expertise and expanded its drone design and manufacturing capabilities through ZenaDrone to innovate and enhance customer inspection, monitoring, safety, security, compliance, and surveying processes.
Job Overview:
We are seeking a detail-oriented and technically skilled QA LiDAR Processing Engineer to support the production and quality assurance of high-quality LiDAR and geospatial datasets. The successful candidate will be responsible for reviewing, validating, and troubleshooting LiDAR processing outputs to ensure they meet project specifications, client requirements, and established quality standards.
This role works closely with LiDAR processing, engineering, and project teams to identify data quality issues, investigate root causes, improve processing workflows, and ensure accurate and consistent delivery of geospatial products.
Key Responsibilities
- Perform quality assurance and quality control (QA/QC) of LiDAR datasets and associated geospatial products.
- Review point cloud data for accuracy, completeness, classification quality, consistency, and conformance with project specifications.
- Validate LiDAR processing outputs, including classified point clouds, digital elevation models (DEMs), digital surface models (DSMs), contours, intensity imagery, and related deliverables.
- Identify anomalies, classification errors, coverage gaps, artifacts, and other data quality issues.
- Conduct horizontal and vertical accuracy assessments using available control and reference data.
- Investigate processing or data-quality issues, determine root causes, and collaborate with processing teams on corrective actions.
- Develop, maintain, and improve QA/QC procedures, checklists, validation tools, and documentation.
- Verify adherence to internal standards, client specifications, and applicable industry or government standards.
- Support the testing and validation of new LiDAR processing workflows, software, algorithms, and automation tools.
- Review processing logs and technical results to identify errors, inconsistencies, or opportunities for optimization.
- Document QA findings and prepare clear quality reports, issue summaries, and recommendations.
- Track identified issues through resolution and verify corrective actions before final product delivery.
- Collaborate with project managers, LiDAR technicians, software developers, and engineering teams to meet project quality and schedule requirements.
- Contribute to continuous improvement initiatives aimed at increasing processing accuracy, consistency, efficiency, and automation.
- Stay current with LiDAR technology, geospatial processing techniques, QA methodologies, and industry best practices.
Qualifications
- Degree or diploma in Geomatics, GIS, Remote Sensing, Geography, Engineering, Computer Science, or a related field, or equivalent relevant experience.
- Experience with LiDAR, point cloud processing, GIS, remote sensing, or geospatial data QA/QC.
- Proficiency with LiDAR/GIS software such as ArcGIS Pro, Global Mapper, QGIS, TerraScan/TerraMatch, LAStools, CloudCompare, or similar tools.
- Understanding of LAS/LAZ formats, coordinate systems, projections, datums, DEMs/DSMs, and spatial accuracy assessment.
- Experience identifying data quality issues, troubleshooting processing errors, and performing root-cause analysis.
- Familiarity with Python, scripting, automation, or automated QA/QC workflows is an asset.
- Strong analytical, problem-solving, organizational, and attention-to-detail skills.
- Effective communication and collaboration skills with the ability to manage priorities and meet project deadlines.
Artificial Intelligence:
We use artificial intelligence to review and screen applications and materials. However, every candidate we move forward with is reviewed and selected, and all final hiring decisions are made by a member of our hiring team.
"We are an equal opportunity employer committed to employment equity utilizing hiring practices on merit and business needs. We encourage applications from women, Indigenous peoples, persons with disabilities, members of visible minorities and all others of legally protected status."
This job post is for an existing vacancy.
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