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
- Design and build cloud-native AWS data platforms supporting mortgage, customer, and
transactional data domains within a regulated financial services environment.
- Build scalable ELT pipelines with AWS Glue, Lambda, Python, and S3, and implement bronze /
silver / gold layers to improve data quality, lineage, and governance.
- Develop dimensional models in Amazon Redshift, reducing reporting latency by 25%;
orchestrate
workflows via Amazon MWAA and monitor with CloudWatch, improving pipeline reliability by
30%.
- Automate infrastructure with GitHub Actions, Terraform, and CloudFormation, and build a cost
optimisation framework across 50+ AWS data workflows.
Data Engineer
Jan 2026 – Mar 2026
RMSI Limited · Reading, UK
- Developed and maintained geospatial data engineering workflows to process, standardise, and
enrich large-scale GIS datasets using Python, GeoPandas, Pandas, NumPy, and FME.
- Performed spatial data validation, reconciliation, and QA, improving reliability of
downstream
analytics and accelerating dataset delivery by ~20%.
Data Engineer
Jun 2021 – Aug 2024
PixelMechanics India Pvt. Ltd. · Ghaziabad, India
- Designed enterprise-scale Azure data platforms using Data Factory, Databricks, Data Lake
Gen2,
Microsoft Fabric, and Synapse Analytics across finance, marketing, and operational domains.
- Built end-to-end ETL/ELT pipelines integrating APIs, transactional databases, and CRM
platforms, implementing Medallion Architecture across bronze / silver / gold layers.
- Built dbt-style transformation frameworks, dimensional models, fact tables, and SCD Type 2
processes; improved data freshness by ~35% via incremental loading, with CI/CD on Azure
DevOps.
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.
View Project →
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.
View Project →
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
