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Parsons is seeking a Data Architect to support the end-to-end delivery of a large-scale Geospatial Digital Twin programme for a major national infrastructure owner in the Middle East. This multi-year initiative will design, build, and operationalize an Operational Digital Twin platform that integrates geospatial data, real-time IoT/SCADA feeds, asset information, and core enterprise systems to enable data-driven planning, operations, and maintenance. The role will work closely with the Solution Architect, Data Governance SME, GIS Development Lead, and a team of international experts, developers, and engineers.
The scope spans discovery and stakeholder engagement, data and information architecture design, proof-of-concept delivery, implementation of a production-grade environment, post-implementation support, and structured training and knowledge transfer. The Data Architect will help define and maintain data and information models, support design of data flows and integration patterns, contribute to master and reference data management, and assist in ensuring that the Digital Twin platform has a coherent, scalable, and well-governed data foundation across all key use cases.
What You’ll Be Doing
Support the Solution Architect and Product Manager in defining and maintaining the data and information architecture for the Operational Digital Twin across discovery, PoC, implementation, and post-implementation support phases, including assessing the quality and fitness-for-purpose of data being ingested.
Assist in developing logical and physical data models for core domains (e.g., assets, networks, locations, work orders, sensors, events), including relationships with geospatial, time-series, and document/BIM data, ensuring models support accurate, consistent, and trusted data.
Help design data flows and integration patterns between the Digital Twin platform and enterprise/operational systems (e.g., EAM/CMMS, ERP, BIM, SCADA/IoT, GIS, data warehouses/lakes), in collaboration with the Integration Lead and Programmer (API), including defining validation checks and quality rules for ingested data.
Perform data profiling and quality assessment on source and ingested datasets to identify data-quality issues (e.g., missing, inconsistent, duplicate, or out-of-range values), and evaluate their impact on the Operational Digital Twin use cases.
Produce clear recommendations and requirements for business and technical teams on how to address identified data-quality deficiencies (e.g., source-system corrections, cleansing rules, enrichment, standardisation, additional controls), and track the implementation and effectiveness of these measures.
Support data-modelling and schema decisions for storage and access across different technologies (relational, time-series, geospatial, and NoSQL/analytical stores), ensuring alignment with performance, scalability, and defined data-quality thresholds.
Assist the Data Governance SME in defining and documenting data dictionaries, business glossaries, and metadata, and in aligning data models and quality rules with governance policies, ownership, and control frameworks.
Help prepare and maintain data-architecture and integration documentation, including models, interface specifications, lineage views, data-quality rules, and design decision records, and support related design reviews with Parsons and client stakeholders.
What Required Skills You’ll Bring
Degree in information management, computer science, engineering, or a related technical discipline from an accredited institution.
Experience contributing to data-architecture or data-modelling activities for large-scale digital, platform, or analytics solutions, preferably in infrastructure, utilities, or urban environments.
Working knowledge of data-modelling techniques and patterns, including conceptual, logical, and physical models, and experience with at least one mainstream data-modelling or diagramming tool.
Basic understanding of geospatial, time-series, and asset/network data, and of how these are used in operational and analytical use cases.
Exposure to enterprise and operational systems such as EAM/CMMS, ERP, BIM, SCADA/IoT platforms, GIS, and data warehouses/lakes, and to common data-integration approaches.
Experience working within multidisciplinary, multinational teams across multiple time zones.
Strong analytical, organisational, and coordination skills, with some experience in structured project or delivery environments (e.g., PMI, PRINCE2, Agile/Hybrid).
Exposure to testing, acceptance, or go-live activities for data platforms or data-heavy solutions.
Excellent communication and documentation skills, with the ability to clearly explain data structures, flows, and trade-offs to both technical and non-technical stakeholders.
Fluency in spoken and written English; Arabic language skills are a strong advantage.
What Desired Skills You’ll Bring
Prior work with national infrastructure owners, transport authorities, utilities, or public works organisations.
Experience working on Digital Twin, smart city, or advanced analytics programmes with complex geospatial and time-series data.
Familiarity with modern data-platform and lakehouse architectures, and with cloud data services on platforms such as Azure or AWS.
Experience working with data-governance frameworks and tools, and collaborating closely with data-governance and cybersecurity teams.
Professional certifications in data management, architecture, or cloud data technologies.
Parsons equally employs representation at all job levels no matter the race, color, religion, sex (including pregnancy), national origin, age, disability or genetic information.
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Founded in 1944, Parsons Corporation, a digitally enabled solutions provider, is focused on creating the future of the defense, intelligence, and critical infrastructure markets. From Earth to outer space, we deliver tomorrow’s solutions today. Equipped with the capabilities required to take on any defense, intelligence, or critical infrastructure challenge, our agile, innovative, and disruptive approach enables us to deliver solutions at the speed of relevance.
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