Senior Digital Twin Data Specialist

Job Purpose
The Digital Twin Data Specialist is responsible for assessing the current Digital Twin data environment, identifying gaps, and designing improved data management processes, delivery specifications, and governance practices for Digital Twin datasets. The role focuses on streamlining onboarding, ingestion, validation, transformation, storage, publishing, and stakeholder data-sharing processes across GISCD’s Digital Twin platform.

Key Responsibilities

• Review the current Digital Twin platform, data management practices, data pipelines, QA/QC procedures, and publishing processes.
• Produce a fact-finding assessment of the current setup and develop a detailed gap analysis with prioritized recommendations.
• Design, model, and document end-to-end data management practices covering onboarding, ingestion, transformation, validation, storage, upload, and publishing.
• Develop Digital Twin data delivery specifications aligned with the existing Digital Twin data model and Dubai BIM standards.
• Define data submission standards for datasets such as buildings, infrastructure, assets, utility networks, landscape, and IoT, including support for multiple LODs, textures, and façade information.
• Recommend and identify areas for automation in the Digital Twin data lifecycle.
• Design and document stakeholder data-sharing processes using BPMN 2.0 at conceptual and detailed levels.
• Guide and direct development of supporting tools and scripts with the automation team using FME, Python, ArcPy, and related technologies.
• Support stakeholder orientation, handover, knowledge transfer, and documentation delivery.
• Perform additional tasks assigned by the GISCD project execution team.

Requirements

Minimum Qualifications

• Graduation from a recognized university or institute.
• Minimum 8 years of experience in the geospatial industry.
• Strong experience with ESRI technologies, including ArcGIS products, ArcGIS Server/Portal, and ArcSDE.
• Strong experience with 3D data and CAD platforms such as AutoCAD.
• Experience with Enterprise Oracle databases and geospatial data pipeline best practices.
• Strong understanding of data ingestion, export, verification, validation, storage, and upload processes.
• Strong understanding of AI/ML techniques for process optimization.
• Excellent English documentation and communication skills; Arabic is preferred.