GIS Intern

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.

• 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.

• 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

• 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 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.