Job Summary The Automated Data Processing team at TomTom builds and maintains scalable cloud-based pipelines that transform raw geospatial data into high-quality map products. We combine geospatial engineering with modern data platforms and emerging AI-driven automation to continuously improve accuracy speed and coverage of our data. We are looking for a curious self-driven Geospatial Intern to join our Automated Data Processing team. This is a great opportunity for a recent or soon-to-graduate student to apply their geospatial education in a real-world industry-scale data processing environment while gaining hands-on exposure to cloud platforms data orchestration tools and Agentic AI-driven automation. The intern will work alongside experienced engineers and analysts contributing to data quality checks pipeline support dashboarding and exploration of AI-assisted workflows. ➡ What you'll do ➡ Support the automated data processing pipeline for geospatial datasets assisting with data validation quality checks and issue resolution. Work with structured and spatial data stored in Postgres/PostGIS databases to query analyze and troubleshoot data. Explore and support use cases involving AWS cloud services for data storage processing and pipeline execution. Contribute to data exploration and transformation tasks using Databricks. Build or enhance Power BI dashboards and reports that turn data quality metrics and pipeline performance into clear business insights — applying data-analysis and reporting skills central to a business analyst role. Analyze existing manual and repetitive workflows identify automation opportunities and contribute to Agentic AI-driven solutions that streamline geospatial data processing — ideal for candidates who enjoy process analysis and workflow optimization. Document processes requirements and findings in clear structured reports to support knowledge sharing and stakeholder communication — a core business-analyst skill applicable across technical and geospatial domains. Collaborate with cross-functional teams (GIS Engineers and Production Engineers) to understand data requirements and pipeline goals. What you'll need ➡ Bachelor's or Master's degree (completed or in final year) in Geoinformatics GIS Geography Computer Science (BCS) or a related technical/analytical field. Basic understanding of geospatial concepts including coordinate systems spatial data formats (Shapefile GeoJSON etc.) and map data structures. Introductory-level familiarity with cloud computing concepts ideally AWS basics (storage compute services). Basic to moderate SQL querying skills with PostgreSQL/PostGIS. Good-to-have basic exposure to Databricks notebooks and data processing. Basic to moderate exposure to Power BI dashboard and report building. Basic exposure to AI/Agentic AI concepts and their application to automating data workflows. Basic programming/scripting knowledge (Python preferred) is a plus Key attributes ➡ Innovative enjoy finding smarter more efficient ways to solve problems. Open-minded comfortable learning new tools technologies and approaches quickly. Explorer mindset curious self-motivated and not afraid to dig into unfamiliar systems or data. Strong communicator and team player who works well in a fast-paced environment. Detail-oriented with a genuine interest in geospatial data and its real-world applications What you'll gain ➡ What You Will Gain Hands-on experience with industry-scale geospatial data processing pipelines. Exposure to modern cloud data engineering and BI tools used in production environments. Early exposure to Agentic AI applications in geospatial data automation a rapidly growing field. Mentorship from experienced geospatial and data engineering professionals. A strong foundation for a career in geospatial data engineering GIS analytics or cloud-based data platforms. ➡