ICT Officer - Geospatial Data Engineer

The ICT Officer – Geospatial Data Engineer provides geospatial data management services to support UN field missions and headquarters. The role involves managing geospatial data workflows, ensuring data quality and governance, and supporting operational planning and decision-making in peacekeeping and political missions worldwide.

Responsibilities

• Develop and deliver geospatial data management services to support UN peacekeeping, political, and humanitarian operations through standardized data management and integration workflows.
• Manage the collection, validation, harmonization, transformation, and maintenance of vector, raster, imagery, authoritative and operational geospatial datasets from multiple sources and environments.
• Support the implementation and maintenance of enterprise geospatial data models, standards, schemas, metadata, and governance frameworks to ensure interoperability and consistency across missions and platforms.
• Manage geospatial data pipelines and automated workflows for data ingestion, processing, synchronization, publication, and distribution across centralized and mission environments.
• Integrate multi-source geospatial and operational data, including satellite imagery, UAV data, IoT feeds, operational datasets, and open-source information into enterprise geospatial systems.
• Maintain and administer geospatial repositories (data lakes/lakehouses), services, and catalogues to support data discoverability, accessibility, lifecycle management, and operational readiness.
• Support data preparation, structuring, and optimization activities required for operational dashboards, situational awareness platforms, mapping services, and analytical applications.
• Implement data governance, stewardship, and access control procedures to ensure compliance with UN policies, security requirements, and operational standards.
• Contribute to the development and application of innovative geospatial data management methodologies, automation tools, and scalable workflows to improve data integration, quality, accessibility, and operational efficiency.
• Implement and optimize ETL/ELT workflows and data integration pipelines to enable efficient, automated, and scalable data processing for enterprise and mission environments.
• Integrate multi-source and multi-format datasets into reproducible and standardized data management environments, ensuring proper documentation, versioning, and traceability.
• Leverage emerging geospatial technologies, cloud-based platforms, and automation capabilities to improve enterprise geospatial data services and operational support.
• Support the implementation of modern geospatial data architectures, interoperability frameworks, APIs, and service-oriented solutions to enable efficient data exchange and reuse.
• Coordinate with clients and stakeholders to translate operational needs into short- and medium-term data management requirements.
• Ensure effective collaboration across technical and operational teams.
• Implement and enforce data quality management frameworks, including validation rules, monitoring mechanisms, and data quality indicators (e.g., accuracy, completeness, timeliness, consistency).
• Contribute to the production and maintenance of high-quality geospatial data products, metadata records, documentation, operational datasets, and reporting outputs using ESRI and related geospatial tools.
• Monitor and troubleshoot data pipelines and datasets to ensure data integrity, reliability, and operational continuity.
• Apply data quality control, validation, and standardization procedures to ensure compliance with enterprise geospatial standards and governance frameworks.
• Ensure compliance with UN standards, operational requirements, information management protocols, and geospatial data governance policies.
• Perform other duties as may be reasonably required and in line with the incumbent’s scope of services.

Requirements

• Advanced university degree (Master’s degree or equivalent) preferably in Computer Science, Data Engineering, Engineering, Information Systems, Geospatial Information Systems (GIS), or a closely related field with 0 years of relevant experience OR a first-level university degree (Bachelor’s degree or equivalent) preferably in Computer Science, Data Engineering, Engineering, Information Systems, Geospatial Information Systems (GIS), or a closely related field with 2 years of relevant experience.
• Demonstrated proficiency in Python scripting for geospatial data management, data processing, and workflow automation, preferably within ArcGIS and related geospatial environments.
• Certifications or training in data quality management, data governance frameworks, or geospatial technologies are a strong advantage.
• Relevant professional certifications in ArcGIS Pro.
• Industry-recognized certifications in data engineering or data architecture (e.g., Microsoft Azure Data Engineer, AWS Data Analytics, Google Professional Data Engineer).
• Relevant experience in data engineering, data pipelines, and data platform management, including modern data architecture or related areas.
• Experience designing and maintaining end-to-end data pipelines (ETL/ELT) and working with data lake, warehouse, or Lakehouse architecture.
• Proficiency in Python, SQL, and data processing frameworks (e.g., Spark or equivalent).
• Professional knowledge of ArcGIS, or comparable GIS software system.
• Experience in data quality management, including validation and monitoring of data quality dimensions (e.g., accuracy, completeness, timeliness).
• Professional experience with GeoAI techniques applied to geospatial data management.
• Familiarity with UN or large-scale operational environments, supporting mission-critical systems.
• Good written and verbal communication skills.
• Ability to document analytical workflows and communicate technical findings clearly to both technical and non-technical audiences.
• Professional experience working on geospatial data processing environments.

Skills

• Python Scripting
• Geospatial Data Management
• ArcGIS
• Data Quality Processes
• Data Governance
• Data Engineering
• Data pipeline design
• ETL/ELT processes
• Data Lake Architecture
• Data Warehouse Schema Design
• SQL
• Data Processing Frameworks
• Spark
• GeoAI
• Geographic Information System
• Workflow Automation
• Technical Documentation Production
• Geospatial Data Processing
• Data Platform Management
• Microsoft Azure Data Engineer certification
• AWS Data Analytics certification
• Google Professional Data Engineer certification

Languages

English