Muhammad Shayan Shamim
I transform raw, scattered data into automated ETL pipelines, structured SQL databases, and interactive Power BI dashboards that drive real business decisions.
About Me
I am a final-year Data Science student at Ziauddin University and a working BI & Data Analyst at Habib University, Karachi. I focus on the practical engineering side of data—building systems that actually drive decisions.
My expertise spans designing automated ETL pipelines with SSIS and Python, structuring reliable SQL Server databases, and delivering interactive Power BI dashboards that business teams genuinely use.
By actively integrating AI workflows and LLMs, I accelerate complex data logic deployment, making backend systems agile and ready for modern enterprise demands.
My current Final Year Project focuses on building an autonomous multi-agent AI pipeline for retail SME automation—integrating Python, ML, LLMs, SQL Server, and Power BI into a single intelligent system.
I operate under the professional standard of XYPEX STUDIO—representing absolute precision in data architecture and a long-term vision for scalable technology services.
Skills & Tools
Work Experience
- Designed and deployed automated ETL workflows using SSIS and Python to extract and incrementally load institutional data into SQL Server.
- Normalized relational databases and engineered robust SQL views, stored procedures, and scalable schemas for downstream reporting.
- Developed interactive Power BI dashboards providing real-time institutional insights to business stakeholders.
- Leveraged AI tools to rapidly deploy complex business logic via Python and SQL, significantly reducing development cycles.
- Gained foundational hands-on exposure to Microsoft Fabric for modern cloud-based data engineering.
View My Work
Click a domain to explore projects, dashboards, and case studies.
Power BI dashboards, ETL pipelines, SQL data models, and KPI reporting systems for real business intelligence.
Python tools, internal apps, REST APIs, and workflow automation scripts built to solve real operational problems.
Agentic AI systems, LLM-powered pipelines, NLP automation, and machine learning models for real-world automation.