Data Engineer / Data Architect

• Design, develop, and own the governed data architecture that supports all EPMO reporting, analytics, and assurance activities. • Build and maintain scalable dimensional data models, including fact tables, dimensions, semantic layers, and reporting-ready datasets. • Design, develop, and manage automated ETL/ELT pipelines integrating data from SAP, Primavera P6, CPCO, DAMAS, and other enterprise systems. • Implement automated data refresh schedules, orchestration processes, incremental loading, monitoring, alerting, and recovery mechanisms. • Lead Primavera P6 data integration, transforming schedule, WBS, resource, and cost data into analytical models. • Develop calculations and models supporting schedule variance analysis, earned value reporting, critical path analysis, float analysis, and progress measurement. • Establish robust data governance standards, including validation rules, reconciliation controls, lineage documentation, and audit-ready processes. • Ensure all reported metrics are traceable from executive reports back to validated source systems through documented transformation logic. • Design and optimize Power BI data models, datasets, measures, security structures, and reporting performance. • Partner with business stakeholders, project controls teams, and analytics teams to translate reporting requirements into scalable data solutions. • Support AI and analytics initiatives by preparing governed, high-quality datasets suitable for AI models, automation, and advanced analytics solutions. • Utilize AI-assisted engineering, anomaly detection, and quality monitoring techniques to improve data reliability and operational efficiency. • Bachelor's Degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Analytics, or a related discipline. • 8-12 years of experience in Data Engineering, Data Architecture, Business Intelligence, Data Warehousing, or Enterprise Analytics. • Strong experience designing enterprise data models, dimensional models, semantic layers, and governed reporting environments. • Advanced SQL expertise including complex joins, CTEs, window functions, merge statements, query optimization, and performance tuning. • Strong hands-on experience with Power Query (M), DAX, Power BI, and enterprise reporting environments. • Experience building and maintaining ETL/ELT pipelines using Microsoft Fabric, Azure Data Factory, SSIS, or similar platforms. • Proven experience integrating enterprise systems such as SAP, Primavera P6, ERP platforms, and project management applications. • Strong understanding of data governance, master data management, lineage, metadata management, data quality frameworks, and reconciliation processes. • Experience supporting construction, EPC, infrastructure, project controls, or large capital project environments is highly preferred. • Practical experience with Python for data processing, automation, validation, and integration activities. • Experience working with version control tools such as Git and modern data engineering practices. • Demonstrated use of AI tools to improve data engineering, data validation, pipeline monitoring, anomaly detection, testing, or documentation processes. • GCC/MENA experience and multi-entity reporting environments are advantageous.