Remote Sensing Engineer

Job Description Process, analyze, and interpret remote sensing data from various sources, including satellite and aerial imagery, to support project objectives in environmental monitoring, land cover mapping, and resource management.Conduct Land Use and Land Cover (LULC) analysis, including image classification, change detection, and thematic mapping, to support projects in agriculture, forestry, urban planning, and natural resource management.Perform accuracy assessments to evaluate the reliability of classification and analysis outputs, using field data and statistical methods to ensure high-quality results.Develop and implement algorithms in Python and utilize Google Earth Engine to automate workflows, analyze large datasets, and extract meaningful information from remote sensing data.Use software tools such as ENVI and SNAP to conduct advanced image processing and analysis, including spectral analysis, vegetation indices, and multi-temporal analysis.Collaborate with project teams to understand data needs, deliver analytical insights, and provide remote sensing support tailored to specific project goals.Prepare detailed reports, maps, and visualizations to communicate findings, including graphical and statistical summaries that meet project requirements.Stay updated on remote sensing technologies, software updates, and industry trends to incorporate the latest methods into workflows, improving analysis accuracy and efficiency.Assist in field validation and data collection as needed, ensuring ground truth data aligns with satellite-based findings for robust analysis.Document methodologies and workflows to standardize processes and support knowledge sharing within the team.QualificationsBachelor’s degree in a relevant field such as Geographic Information Science (GIS), Geospatial Information Technology, Geomatics Engineering, Geodesy, Environmental Science, or a related field.1-2 years of experience in remote sensing data analysis and processing.Proficiency in remote sensing data processing, with proven skills in Land Use and Land Cover (LULC) analysis.Familiarity with Python programming.Experience working with Google Earth Engine.Strong working knowledge of remote sensing software, such as ENVI or SNAPExcellent problem-solving abilities and a high level of attention to detail in data analysis, ensuring accuracy and reliability in outputs.Good communication skills to present analytical findings clearly and collaborate with cross-functional teams.Strong time management skills with the ability to meet project deadlines and work effectively both independently and as part of a team.