About Me
A passionate data professional and content creator dedicated to building ethical, scalable solutions
Location
England, UK 🇬🇧
Education
MSc Data Science
University of Glasgow • Merit
B.Tech IT
Amity University • First Division
Certifications6+ CERTS
Awards & Recognition
As a Data Engineer at Central Co-op and a passionate data science graduate from the University of Glasgow, I thrive at the intersection of cloud engineering, machine learning, and responsible AI. I specialize in building secure, scalable data pipelines using tools like Microsoft Fabric, Azure, and AWS.
With hands-on experience across diverse domains—from deep learning research and economic policy analysis to enterprise data architecture—I bring a versatile skillset and a mindset for continuous improvement. I'm always excited to collaborate on projects that are technically robust and purpose-driven.
Professional Experience
3+ years of hands-on experience building robust data solutions across diverse industries
Data Engineer
- Built automated data pipelines using Azure Data Factory and SQL, integrating APIs and file-based workflows
- Resolved ETL failures from schema mismatches, access errors, and credentials; added robust logging
- Optimized ingestion via parallel processing and version-controlled deployment using Git
- Automated ingestion using Azure Functions, monitored via Airflow; reduced latency by 30%
- Collaborated with IT, BI, and finance teams to ensure secure, compliant data pipelines
Research Data Assistant
- Conducted curriculum mapping using Excel and data models to identify interdisciplinary learning gaps
- Analysed life expectancy factors under the SIPHER project using QCA methodology
- Applied fuzzy-set QCA to model outcomes and derive health policy insights
- Wrote R scripts for causal extraction; contributed to a forthcoming publication
Platform Engineer
- Integrated Python and SQL with SAP Hana S4 to improve data quality and real-time insights
- Improved ETL efficiency by 25% and reduced inconsistencies by 20% via CI/CD restructuring
- Built Tableau dashboards to validate data integrity with cross-functional teams
- Managed GitHub repositories, reviewed PRs, and enforced engineering code standards
Python Cloud Developer
- Built emotion recognition models using OpenCV and TensorFlow; improved performance by 40%
- Developed Emojify, a Dockerized AI tool for streamlined deployment and scalability
- Automated model evaluation in Python; deployed inference pipelines on AWS EC2
Featured Projects
A showcase of data engineering, machine learning, and cloud computing projects
Developed a Python-based bike rental app with map interface, multi-role access (User/Operator/Manager), secure authentication, wallet system, and comprehensive reporting. Features real-time bike tracking and admin dashboard.
Built a multiview visualization system for U.S. traffic accident data analysis (2016-2023). Features interactive maps, temporal analysis, weather correlation studies, and geographic hotspot identification with advanced filtering capabilities.
Analyzed spatial distribution of geo-tagged tweets in London using 1km x 1km grids. Implemented newsworthiness scoring mechanism and performed statistical analysis of tweet distribution patterns across the city.
Built a fully functional AI chatbot with 98% accuracy using neural networks and NLP. Features multiple interfaces (terminal, GUI, testing), sub-second response times, and 11 conversation categories with professional-grade performance.
Production-grade streaming pipeline for real-time retail analytics with sub-second latency. Implements Kappa architecture using Kafka, Spark Structured Streaming, and PostgreSQL for windowed aggregations with 180+ events/min throughput.
Experimented with differential privacy in deep learning for human activity recognition using UCF101 dataset. Analyzed trade-offs between privacy protection and model performance, achieving balanced results with data augmentation techniques.
Get In Touch
I'm always excited to collaborate on projects that are technically robust and purpose-driven. Let's connect if you're building something meaningful with data!