Muhammad Sobaan Hussain Shah

Designed and automated ETL pipelines using Python and SQL, improving data freshness and reducing
manual reporting effort by 40%.
Built scalable ingestion and preprocessing pipelines for 1, 400+ machine sensor files (6-axis vibration
data), enabling downstream ML anomaly detection models.
Optimised SQL queries and database structures, reducing execution times by 25-35% across critical
reporting tables.
Developed and deployed automated KPI dashboards (Tableau + SQL), saving operations teams ~20
hours/week in manual reporting.
Implemented Python automation scripts (pandas workflows) that reduced large-dataset processing time
from hours to minutes.
Contributed to predictive modelling projects, improving forecast accuracy by 10%.
Led data governance initiatives including validation frameworks, audit trails, and standardised data
dictionaries.

Designed and deployed secure relational databases with role-based access and GDPR-compliant
processes for 50+ staff.
Improved query performance by 25% through indexing and optimisation.
Created user-friendly front-end interfaces for non-technical staff.