Muhammad Hamza is a pragmatic Data & AI engineer with eight years of cross-functional experience turning messy datasets and vague stakeholder requests into production AI and data pipelines. He builds end-to-end solutions—from PySpark medallion architectures and Airflow orchestration to Azure OpenAI-powered RAG chatbots and YOLOv8 vision models—while translating business intent into prioritized Jira backlogs. At Al Ghurair he shipped semantic policy retrieval and document intelligence systems that cut compliance lookup time by 70%, and at Cavendish Maxwell automated property pipelines that saved 40% of prep time. Comfortable jumping between analytics, engineering, and product, he thrives where processes are broken and “figure it out” is the brief. Open to Data/AI engineering roles across Canada and remote, he blends hands-on coding with stakeholder diplomacy to drive measurable operational impact.
Contributions:2 pushes, 1 branch in 4 years 4 months
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