About Me
A passionate data professional and content creator dedicated to building ethical, scalable solutions
Location
United Kingdom 🇬🇧
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
Data Consultant
- 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.
Built privacy-preserving ML models for human activity recognition using UCF101 video dataset. Implemented four model variants comparing differential privacy vs non-DP approaches with data augmentation. Used TensorFlow, Opacus, and PyTorch to analyse accuracy-privacy trade-offs with ROC curves, confusion matrices, and F1 scores.
Get In Touch
Whether you'd like to explore my projects in detail, discuss emerging trends in data engineering across UK industries, or collaborate on innovative solutions—I'd love to hear from you. Let's connect and turn ideas into impactful outcomes!