greehill

• Vectorization of 2D data.
• Manual 2D/3D GIS data manipulation.
• QA/QC of point cloud classification.
• Database handling.
• Editing and preparing of 2D vector and 3D point cloud data for further processing.
• Documentation creation (standard operation procedure, training documents, other technical documentation).
• Work management tasks with external contractors and teams.

GIS Operator

Engineering Manager

• Hands-on Technical Leadership
• Remain actively involved in architecture, system design, and selected critical implementations
• Guide engineers through complex problem-solving, technical trade-offs, and system evolution
• Drive adoption of modern technologies to improve engineering productivity and quality
• Ensure systems are designed for scalability, multi-tenancy, and long-term maintainability
• Lead code and design reviews, maintaining a consistently high engineering standard
• AI-enabled Engineering
• Define and implement a structured approach to AI adoption across engineering workflows.
• Ensure AI usage is embedded in daily workflows rather than ad-hoc: AI-assisted coding, reviews, and refactoring
• Automated test generation and QA acceleration
• Intelligent debugging and root cause analysis
• Measurable (productivity, defect reduction, cycle time)
• Secure and compliant adaption
• Drive consistency in tooling and practices across teams to avoid fragmentation
• Delivery & Execution
• Own delivery predictability across multiple parallel initiatives
• Balance delivery speed, quality, and technical debt
• Ensure prioritization is clear and aligned with business objectives
• Actively manage cross-team dependencies and integration points
• Transition teams from reactive execution to structured, planned delivery
• Engineering Process & Standardization
• Establish scalable and consistent engineering processes: Sprint planning, backlog management, and delivery tracking
• Release management with rollback capabilities
• Incident, problem, and change management discipline
• Introduce practical standards that improve speed and reduce ambiguity without over-engineering
• Reduce reliance on individuals through improved documentation, automation, and knowledge sharing
• Team Development & Scaling
• Build and scale a high-performing engineering team
• Coach engineers and develop emerging technical leaders (senior engineers, tech leads)
• Increase delegation and distributed ownership to remove bottlenecks
• Strengthen accountability and outcome-oriented delivery culture
• Quality, Reliability & Performance
• Improve system reliability through better engineering practices and architectural discipline
• Ensure a scalable testing strategy across units, integration, regression, and automation layers
• Partner with DevOps/SRE to strengthen observability and operational excellence
• Drive continuous improvement through incident learnings and performance insights

Engineer

• Design and implement algorithms to process and analyze sensor data from sources like LiDAR, images, and satellite imagery, extracting meaningful information about urban trees and environments.
• Create algorithms to transform sensor data into actionable insights, such as reconstructing 3D models, segmenting spatial data, or detecting environmental features.
• Develop techniques for preprocessing raw sensor data, including noise filtering, sampling, and quantization, to ensure data quality and usability.
• Optimize algorithms for performance and scalability to handle large, complex datasets efficiently.
• Integrate data from multiple sensor types to enhance the accuracy and detail of digital representations.
• Contribute to the continuous improvement of our data processing tools, methods, and pipelines.
• Stay informed about advancements in sensor data processing, computer vision, and geospatial analysis to bring fresh ideas to the team.

GIS Operator

Engineering Manager

Algorithm Engineer – Sensor Data Processing