Data Engineer

Work Arrangement: On-site

About the Opportunity

XML International is recruiting an experienced Geospatial Data Engineer – Data Integration & Generalization Specialist to develop and maintain automated geospatial data workflows within an international technology environment.

This role focuses on integrating, validating, harmonizing and transforming geographic information from multiple authoritative sources into reliable, high-quality spatial datasets.

We are seeking a technically strong professional with hands‑on experience in Python, spatial SQL, GIS automation and spatial data processing, particularly in the areas of topology validation, geometry processing and multi‑scale generalization.

Key Responsibilities

Geospatial Data Integration & Harmonization

• Integrate geographic datasets from multiple authoritative and open data sources.
• Harmonize data schemas, identifiers and attributes to establish consistent spatial structures.
• Develop reliable processes for spatial data transformation, matching and validation.
• Maintain data consistency, accuracy and traceability across integrated datasets.
• Design, develop and maintain automated Python-based geospatial data pipelines.
• Implement workflows for geometry processing, spatial matching and continuous data validation.
• Improve the reliability, performance and scalability of geospatial processing operations.
• Automate repetitive GIS processes and establish reusable data engineering solutions.
• Develop and automate cartographic generalization processes across multiple map scales.
• Apply topology-preserving simplification, aggregation and feature-selection techniques.
• Validate spatial topology, identify geometry errors and implement automated repair processes.
• Maintain the integrity and consistency of vector datasets throughout processing workflows.
• Manage multi-scale geographic datasets and maintain historical change records.
• Track official boundary updates, data lineage and dataset revisions.
• Perform coordinate transformations and prepare spatial datasets for different map projections.
• Optimize geographic datasets for standardized geospatial web services and distribution.

Quality, Automation & Documentation

• Implement automated testing and quality assurance procedures for spatial data pipelines.
• Apply version control and structured data-release practices.
• Collaborate with technical teams to resolve complex geospatial data challenges and improve processing workflows.

Required Qualifications & Experience

• Bachelor's degree in GIS, Geomatics, Computer Science, Data Engineering or a related quantitative field.
• Minimum 5 years of professional experience in geospatial data engineering and automated spatial data processing.
• Advanced proficiency in Python and spatial SQL.
• Strong experience with automated GIS geoprocessing workflows.
• Proven experience in vector data integration, topology validation, geometry repair and automated generalization.
• Hands‑on expertise with ArcGIS Pro, ArcPy or equivalent geospatial processing technologies.
• Experience working with enterprise spatial databases.
• Strong analytical and technical problem-solving skills.
• Professional fluency in written and spoken English.
• Ability to work independently and collaborate effectively with cross‑functional teams.
• Strong technical documentation and data quality management practices.

Desirable Technical Experience

• GeoPandas, Shapely and GDAL/OGR.
• PostGIS or FME.
• Automated boundary management and change detection.
• Specialized map projections, including Equal Earth.
• Vector tiles and OGC web standards.
• Git version control and CI/CD automation.

What We're Looking For

The ideal candidate combines geospatial engineering expertise with strong software development and data automation capabilities.

You should be comfortable processing complex vector datasets, building Python-based pipelines, validating spatial topology and implementing reliable data transformation workflows.

Experience automating spatial generalization and maintaining geographic datasets across multiple scales will be particularly valuable.

Why Consider This Opportunity?

• Work with complex geospatial datasets and enterprise GIS technologies.
• Develop automation solutions that improve spatial data accuracy and consistency.
• Apply advanced Python and spatial database expertise.
• Contribute to scalable geographic data processing and distribution systems.
• Collaborate with technical professionals in an in