Chinedu
Agwunobi

• Designed, built, and maintained cloud-based ETL/ELT pipelines using AWS Glue, Lambda, and Azure Data Factory, delivering scalable data integration solutions across the full development lifecycle.
• Automated data validation, profiling, and cleansing workflows, reducing manual intervention by 20 hours per week and strengthening data quality governance.
• Led a cloud migration project achieving a 15% reduction in infrastructure costs while improving security and architectural standards.
• Led peer code reviews and pipeline design reviews, maintaining high standards of quality within an Agile delivery environment.
• Collaborated with analysts, business stakeholders, and technical teams to ensure data solutions met user requirements and aligned to organisational goals.

• Built and optimised big-data pipelines in Azure Databricks, improving model performance and enabling more accurate segmentation with a 25% improvement in accuracy.
• Improved SQL query logic and efficiency, reducing execution times by 30% and improving reporting responsiveness.
• Supported data ingestion and modelling tasks for analytics teams, ensuring accuracy and consistency across datasets.

• Applied clustering techniques including K-Means, DBSCAN, and Hierarchical Clustering to analyse the Mall Customer Dataset in R-Studio, identifying distinct customer segments to support targeted marketing strategies.
• Developed Python-based data preprocessing pipelines, reducing missing data issues by 30% and improving downstream modelling outcomes.
• Implemented effective data visualisation techniques to communicate insights derived from complex datasets to non-technical stakeholders.
• Created operational dashboards in Power BI, enabling evidence-based decision-making across teams.
• Conducted extensive research into cutting-edge data science techniques, applying findings to improve analytical methodologies.
• Collaborated with cross-functional stakeholders to interpret analytical outcomes and improve data visibility across the organisation.

Advanced postgraduate study covering machine learning, big data analytics, statistical modelling, NLP, and deep learning. Dissertation: "Empowering Market Forecasting and Investment Decisions with Advanced Sentiment Analysis Techniques."