Data, Power BI and AI Specialist

About OSUS:

Our journey began in 2006 in the city of Riyadh, driven by an ambitious vision to lead the next generation of commercial, residential, and mixed-use real estate projects. Since then, we have continued to establish our presence as a developer redefining the concept of real estate development through projects rooted in integration, innovation, thoughtful design, and modern technological solutions that elevate the end-user experience, whether individuals or businesses. We believe that mixed-use developments represent the future of urban planning. Guided by this vision, we create projects that merge urban functions into a single space, reshaping daily life in a more efficient and flexible way. We design vibrant destinations where living and working intersect, and where commercial and entertainment facilities harmonize within an integrated environment, fulfilling individual aspirations and supporting the growth of modern communities. At OSUS, we continue to build on this approach, inspired by Saudi Arabia’s Vision 2030 and committed to developing real estate solutions that elevate the urban landscape, meet the ambitions of individuals and investors, and align with the evolving nature of cities and future lifestyles.

Job Summary:

Establish and run a centralized data, BI, and AI capability for the organization. You build a unified data platform that supports ingestion, transformation, analytics, and AI driven insights. You enable data driven operations and decision making across real estate investment, development, construction, project management, sales, leasing, facility management, customer support, and call center functions. You own BI delivery, Power BI dashboards, Power Apps solutions, and AI augmented insights including LLM based use cases.

Responsibilities are not limited to:

• Lead end to end delivery of large scale IT and digital initiatives.
• Define project scope, objectives, success metrics, and delivery plans.
• Manage project budgets, timelines, risks, and dependencies.
• Coordinate cross functional teams including IT, business, vendors, and regulators.
• Ensure alignment with enterprise architecture, security, and compliance standards.
• Drive application integrations and data consistency across platforms.
• Apply Agile, Waterfall, or hybrid methodologies based on project needs.
• Track progress using dashboards and reports for executive stakeholders.
• Proactively identify issues and implement corrective actions.
• Ensure smooth handover to operations and support teams.
• Continuously improve project management practices and tools.
• Design and implement end-to-end data pipelines using Microsoft Fabric Data Engineering.
• Develop and optimize Delta tables for analytics and reporting.
• Implement medallion architecture (Bronze, Silver, Gold layers).
• Design, develop, and maintain Power BI reports and dashboards.
• Build interactive visualizations for executive, operational, and analytical use cases.
• Create and manage Power BI semantic models (datasets).
• Implement DAX measures and calculated columns for advanced analytics.

Key Deliverables:

• Approved project charters and detailed project plans.
• On time and on budget project delivery.
• Integrated and compliant IT solutions.
• Executive level status reports and decision dashboards.
• Post implementation reviews with clear lessons learned.

Qualifications:

• Bachelor’s degree in Computer Science, MIS, IT, Data Science, or related field.
• 3-5 years of experience in BI, analytics, and data solutions.
• Minimum 3 years in BI, AI and analytics delivery roles.
• Hands on experience designing and implementing enterprise data warehouses and data lakes.
• Experience in real estate industry analytics is strongly preferred.
• Strong experience building end-to-end data pipelines.
• Hands-on with Azure Data Factory / Microsoft Fabric pipelines.
• Experience with Spark (PySpark, Spark SQL), MS SQL and Delta Lake.
• Handling APIs, incremental loads, and error handling.
• Designing enterprise Power BI semantic models.
• Advanced DAX (time intelligence, optimization).
• Data modeling (star schema, relationships).
• Performance tuning and large dataset handling.
• Implementing Row-Level Security (RLS).