Data Engineer with 4+ years of experience building scalable data platforms across financial services and
mortgage lending. I currently deliver AWS-based data solutions and analytics-ready datasets, with deep
expertise in ETL/ELT pipelines, dimensional modelling, and cloud data warehousing.
I've designed and operated end-to-end pipelines on both AWS (Glue, Lambda, Redshift, S3, MWAA) and Azure
(Data Factory, Databricks, Synapse, Data Lake Gen2), implementing Medallion (bronze/silver/gold)
architectures, Star and Snowflake schemas, and SCD Type 2 processes for accurate historical reporting.
I hold an MSc in Data Science (Distinction) and am passionate about building governed, cost-efficient
data products that support trusted reporting and strategic decision-making.
Core Skills
Experience
Data Engineer
Mar 2026 – Present
Coventry Building Society · Coventry, UK
Data Engineer
Jan 2026 – Mar 2026
RMSI Limited · Reading, UK
Data Engineer
Jun 2021 – Aug 2024
PixelMechanics India Pvt. Ltd. · Ghaziabad, India
Projects
Built an end-to-end forecasting framework to predict daily acute respiratory illness counts from
UK air quality data. Used STL seasonal-trend decomposition to separate winter seasonality from
residuals, engineered 1-7 day distributed lag features for delayed exposure effects, and
compared Random Forest, XGBoost, and LSTM models with time-aware validation. SHAP analysis
identified PM2.5 and NO2 as the dominant predictors, with O3 more influential in warmer months.
View Project →
Built a Python ML pipeline to predict credit card defaults on an imbalanced UCI dataset.
Preprocessed the data, tuned a Random Forest model to handle class imbalance, and achieved a
0.76 ROC-AUC score, with visualizations to communicate key drivers. Next step: deploy via
Flask/Streamlit and add SHAP/LIME for model explainability.
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Built a scalable stroke-prediction model using PySpark MLlib to handle large-scale health data.
Addressed class imbalance with SMOTE, identified the key health indicators driving risk, and
built an interactive Tableau dashboard to visualize patterns for better health outcomes.
View Project →
Cleaned and modeled a dataset of 150,000+ U.S. electric vehicle records with SQL and Python, then
built an interactive Tableau dashboard with maps and trend charts tracking EV adoption from
2011-2024, highlighting growth patterns and regional hotspots.
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Built an HR analytics dashboard to explore employee attrition. Cleaned and prepared the data in
Python, then visualized it in Power BI with KPIs, heatmaps, and drill-down filters, surfacing
low job satisfaction and poor work-life balance as key attrition drivers to support retention
strategy.
View Project →
Built a hand-gesture detection model using TensorFlow's Object Detection API with SSD MobileNet
v2, then converted it to TFLite for real-time mobile deployment. Evaluated performance with mean
Average Precision (mAP), demonstrating efficient computer vision on resource-constrained
devices.
View Project →
Certifications
Here are some certifications I've earned that demonstrate my skills in data science and analytics:
Education
MSc in Data Science — Distinction
Sept 2024 – Sept 2025
Coventry University · Coventry, United Kingdom
Beyond the Data
Pipelines and dashboards are only half the story. Away from the terminal, here's what keeps me
curious, competitive, and good company.
Football
On the pitch most weekends — competitive, team-first, and always up for a game. It's how I
switch off and stay sharp.
Literature
A devoted reader of Russian and existential fiction — Dostoevsky, Kafka, and the long,
uncomfortable questions they refuse to answer neatly.
Always Learning
I spend downtime experimenting with new tools and techniques — from LLM-powered data
workflows to whatever's next in the AWS/Azure ecosystem. Staying curious is part of the job.
