A diligent Spatial Data Analyst converts complex geospatial datasets into clear, actionable insights. This role supports planning, operations and research by preparing maps, conducting spatial analysis and ensuring data quality. The ideal candidate combines technical GIS expertise with strong analytical thinking and effective communication skills. They will work across teams to deliver location intelligence that supports business decisions and project delivery.
The Spatial Data Analyst role involves managing geographic information systems to produce accurate spatial datasets, analyses and visualisations that inform strategic programmes and operational tasks.
Spatial Data Analyst Job Profile
The Spatial Data Analyst collects, cleans and integrates geospatial data from multiple sources, maintaining data integrity and documentation. They create maps, spatial models and reports to support decision making across sectors such as transport, environment and utilities.
Working closely with project managers and subject matter experts, the analyst ensures that spatial outputs meet technical standards and user needs. They often support field surveys, database administration and automation of routine geoprocessing tasks.
Spatial Data Analyst Job Description
The Spatial Data Analyst is responsible for developing and maintaining GIS databases, performing spatial analysis and generating cartographic products. This includes digitising features, georeferencing datasets, conducting spatial joins and running spatial statistics to uncover patterns and trends. The role requires proficiency with desktop GIS software and an understanding of spatial data models and projections.
Analysts prepare clear, publication-quality maps and interactive visualisations to communicate findings to technical and non-technical stakeholders. They produce regular reports and dashboards, explaining methodology, assumptions and limitations. The role also involves scripting and automation to streamline workflows and improve reproducibility of analyses.
Collaboration is central to the position. The analyst liaises with data providers, engineers and planners to gather requirements, validate results and implement improvements. They contribute to data governance, setting standards for metadata, version control and quality assurance to ensure datasets are reliable for long term use.
Spatial Data Analyst Duties and Responsibilities
- Collect, import and preprocess spatial data from surveys, satellite imagery and public datasets.
- Maintain and update GIS databases, ensuring correct projections, topology and metadata.
- Perform spatial analyses such as buffering, overlay, network analysis and spatial interpolation.
- Create high-quality maps, charts and interactive visualisations for reports and presentations.
- Develop scripts and automation using Python, R or similar to streamline geoprocessing tasks.
- Conduct data quality checks and document data lineage and methodology.
- Collaborate with cross-functional teams to translate business questions into spatial solutions.
- Provide technical support and training to colleagues on GIS tools and best practices.
- Support procurement and evaluation of spatial data sources and third-party services.
Spatial Data Analyst Requirements and Qualifications
- Bachelor's degree in geography, geomatics, GIS, environmental science, urban planning or related field.
- Strong experience with GIS software such as Esri ArcGIS Pro, QGIS or similar platforms.
- Proficiency in spatial scripting and automation using Python, R or SQL.
- Understanding of coordinate reference systems, geoprocessing and spatial data models.
- Experience with remote sensing, LiDAR or satellite imagery processing is desirable.
- Familiarity with spatial databases such as PostGIS and cloud GIS services is an advantage.
- Excellent analytical skills with attention to detail and a methodical approach to data quality.
- Strong written and verbal communication skills with the ability to present technical findings clearly.
- Ability to prioritise tasks and work independently as well as part of a team.
- Relevant professional certifications or demonstrable project portfolio preferred.
