Data Engineer / Data Architect

Job Summary

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

Qualifications

• 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.