Resume · Data Engineer
James
Adeshina
Data Engineer specialising in cloud pipelines, ETL/ELT, data modelling and analytics-ready systems across AWS, Azure and BigQuery.
Download CV ↗Profile
Data Engineer and research-focused practitioner with an MSc in Big Data Analytics (Distinction), working across data engineering, analytics and applied AI. My recent work at the University of Derby includes building backend data flows for AI-DRA, analysing structured rehabilitation datasets, and developing NLP pipelines for large-scale consultation-response analysis. I work primarily with Python, SQL, cloud and BI tooling, with a strong focus on reliable data preparation, modelling, quality and decision-support.
Professional Experience
University of Derby
Derby, England, United Kingdom · Hybrid
Research Assistant | AI & Computer Vision
Part-time · University of Derby
Contributing to the development of AI-DRA, an AI-powered digital rehabilitation platform designed to support stroke survivors.
- Developed and refined a full-stack digital health prototype integrating AI-based movement recognition with application and backend data services.
- Built backend data flows using Supabase to support user accounts, rehabilitation sessions, movement results and progress-tracking functionality.
- Worked with structured rehabilitation data and application state to capture and surface metrics including movement scores, accuracy and session progress.
- Implemented computer vision and movement-recognition logic to analyse rehabilitation activities and generate task-specific feedback.
- Integrated frontend, application and data-layer components to support Survivor, Carer and Admin workflows.
- Tested and refined system functionality based on usability feedback, while documenting implementation decisions and development processes.
Data Engineering & Analytics Research Assistant | Health & Performance Analytics
Part-time · University of Derby
Collaborated with physiotherapists to analyse movement-screening data and develop data-driven insights supporting health and performance assessment.
- Processed and analysed data from 46 participants across 22 biomechanical and demographic variables using Python.
- Engineered five clinically relevant features, including Asymmetry Score and Pain Flag, to support identification of movement dysfunction and risk profiles.
- Performed 15 exploratory analyses examining relationships between participant characteristics and bilateral movement performance.
- Developed structured analytical workflows for cleaning, transforming and preparing movement data for downstream analysis and reporting.
- Built an interactive Power BI dashboard with 12 visuals, including pain-risk tracking and drill-through functionality to support movement assessment.
- Assessed feature stability, clustering patterns and variance to evaluate the feasibility of future explainable injury-risk modelling.
NLP & Data Engineering Research Assistant
Full-time · University of Derby
Developed an end-to-end NLP and data-processing prototype for a UK local authority to automate the analysis of public consultation responses.
- Built a processing pipeline for approximately 987 scanned consultation letters, covering OCR extraction, text cleaning, preprocessing and structured preparation for downstream analysis.
- Developed annotation and data-augmentation workflows using manually labelled data, LLM-assisted annotation and 1,300+ synthetic consultation responses to support model development and class balancing.
- Generated semantic text embeddings using SentenceTransformers and developed supervised machine learning pipelines for consultation-response classification.
- Trained and evaluated a binary classifier for Objection and Suggestion responses, achieving approximately 94% held-out accuracy.
- Designed a multi-label classification approach to identify issues across Environment, Health & Safety, Infrastructure, Community, and Economy & Property categories.
- Integrated LLM-based summarisation, sentiment interpretation and natural-language question answering to generate actionable insights from consultation responses.
- Developed a Streamlit interface to present classifications, summaries, sentiment insights and individual response analysis to non-technical stakeholders.
- Reduced analysis time for a stress-test batch of consultation responses from approximately 6–10 hours of manual review to under one minute through automated processing.
Selected Projects
Explainable AI for Diabetes & Pre-diabetes Detection
Built an ML training pipeline processing 100k+ hospital records, with feature engineering, validation, Logistic Regression, Random Forest, XGBoost and SHAP-based interpretability.
View projects ↗Monzo User Sentiment & Feature Insights
Engineered a Python–BigQuery workflow for 33k+ app-store reviews with automated sentiment and keyword extraction, then served enriched data to Power BI.
View case study ↗Retail Sales Integration Pipeline
Developed an automated ELT workflow using AWS S3, Python, Airbyte and MotherDuck, with schema validation, record-count checks and SQL profiling.
View projects ↗AI-DRA Digital Rehabilitation Assistant
Applied computer vision, ML and structured data workflows to support rehabilitation analysis, progress tracking and accessible user feedback.
View case study ↗Technical Skills
Programming & Query
ETL, Orchestration & Cloud
Modelling, Lakehouse & BI
Automation, Governance & Supporting ML
Education
MSc Big Data Analytics
University of Derby
Modules included Processing Big Data (90%), Business Analytics (84%) and NLP (80%).
Dissertation: Explainable AI for Diabetes and Pre-diabetes Detection: Integrating SHAP and OpenAI GPT-4 for Human-Centred Explanations (84%).
BSc Computer Science & Information Technology
Bowen University · Second Class Upper · CGPA 3.61/4.00
Final-year project: AI-driven diagnostic chatbot for early-stage lung cancer detection.
Achievements & Certifications
Hackathon Winner — Insights Engineer Role
Virgin Media O2
Designed a data transformation pipeline for anonymised telecom datasets and optimised Power BI dashboards using DAX and SQL for fast analytical performance.
Selected Technical Learning
- AWS Certified Data Engineer Associate (DEA-C01) — LinkedIn Learning
- AWS Certified Cloud Practitioner (CLF-C02) — LinkedIn Learning
- Microsoft Azure Fundamentals (AZ-900) — LinkedIn Learning
- Complete Guide to Google BigQuery for Data and ML Engineers — LinkedIn Learning
- Apache PySpark by Example — LinkedIn Learning
- Docker for Data Engineers — LinkedIn Learning