GIS Tech Lead (FME + ArcGIS)

As the GIS Tech lead, you will be responsible for leading our FME and GIS analyst team. You will provide technical guidance on complex projects, design FME workbenches and workflows, and ensure data quality. Your role involves overseeing the design, development, and maintenance of FME workbenches for efficient data processing. You will also lead the development and review of Python scripts to enhance FME workflows and functionalities. In this position, you will mentor and guide analysts in effectively utilizing ArcGIS tools and techniques for data management, analysis, and visualization. You will review FME errors and ArcGIS model schema issues, identifying and correcting critical errors to ensure data quality and integrity. Implementing robust QA/QC procedures will be crucial to ensure all data products meet the highest standards of accuracy and completeness. Your responsibilities will also include managing and prioritizing project tasks, assigning workloads to analysts based on skillsets and project requirements. Tracking project progress and ensuring timely delivery of data products within established deadlines will be essential. Collaboration with internal stakeholders to understand data needs and develop optimal solutions is a key aspect of this role. To stay up to date with the latest advancements in FME, ArcGIS, and geospatial technologies, you will need to continuously learn and adapt. Documenting best practices, workflows, and procedures for knowledge sharing and future reference will be important for the team's success. The ideal candidate for this position will have a minimum of 8+ years of hands-on experience in performing spatial analysis and delivering solutions using ArcGIS and FME. Proven experience in leading and mentoring a team of GIS and FME analysts is required. In-depth knowledge of FME workbenches, data transformation techniques, and Python scripting for automation is essential. A strong understanding of ArcGIS Desktop applications and geospatial data models is necessary. Experience in designing and implementing robust QA/QC procedures for geospatial data, excellent project management skills, solid problem-solving and analytical skills, effective communication and collaboration skills, and experience in Agile development methodologies will all be valuable assets in this role.,