Data Engineer | Data Analyst
I specialize in designing scalable data pipelines and transforming complex data into strategic insights that drive business decisions through advanced analytics and compelling visualizations.
I am a data professional with expertise in building robust data infrastructure and extracting meaningful insights from complex datasets. With a background in computer science and artificial intelligence, I help organizations make data-driven decisions by leveraging tools like Python, SQL, Snowflake, Tableau, and Airflow.
Beyond tech, I'm passionate about continuous learning and helping others succeed. I am a calm person who enjoys reading books, watching movies, listening to gospel music, and playing games. My faith and values shape how I approach both work and relationships.
I believe in the power of data to solve real-world problems and drive innovation. I combine engineering best practices with analytical thinking to build systems that bridge the gap between complex data and meaningful insights, making analytics accessible and actionable for businesses and individuals alike.
Through my work, I aim to contribute to projects that have a positive impact on society while continuously learning and adapting to the evolving data landscape.
I enjoy building scalable data pipelines and integrating data sources to support analytics and machine learning workflows. My experience includes ETL automation, data modeling, and warehousing using tools like Python, SQL, Snowflake, and Airflow.
I am passionate about uncovering insights through data. From cleaning and transforming datasets to building dashboards and reports, I use tools like Excel, Tableau, and SQL to help stakeholders make informed decisions backed by data.
I explore machine learning solutions for classification, regression, and prediction tasks. I've worked with Scikit-learn, TensorFlow, and PyTorch to train and evaluate models that drive business impact.
I have a deep interest in language models and text analysis. I've used NLP techniques for summarization, classification, and semantic search using tools like Hugging Face Transformers, NLTK, and vector similarity techniques.
Python
MySQL
PostgreSQL
Tableau
Excel
Matplotlib
Pandas
Metabase
Snowflake
Apache Airflow
SQL Server
Scikit-learn
Hugging Face
Asana
ClickUp
Draw.ioA selection of data engineering pipelines, analytics dashboards, and ML solutions I've built end-to-end.
Built enterprise-grade SQL data warehouse using Medallion Architecture to process and transform 60K+ raw ERP/CRM records through advanced T-SQL ETL pipelines and comprehensive validation frameworks, achieving 99.9% data quality improvement while delivering performance-optimized star schema that reduced complex analytical query runtime from hours to minutes and enabling real-time business intelligence for data-driven decision-making.
T-SQL
SQL Server
Git
Draw.io
Developed a comprehensive Excel analytics dashboard with advanced formulas, pivot tables, and interactive filtering to analyze coffee sales across customers, regions, and time periods, uncovering critical business insights including loyalty program inefficiencies and regional market opportunities that informed strategic recommendations for revenue optimization.
Excel
Dashboard Design
Architected an automated end-to-end data pipeline using Python, Docker-containerized Airflow, and Snowflake to extract, transform, and load beauty purchase data from Google Sheets. Weekly ETL orchestration loads to a snowflake schema with 7+ dimensions and optimized stored procedures that enabled real-time Tableau analytics for spending trend analysis, budget optimization, and data-driven purchase decision-making.
Python
Snowflake
Airflow
Tableau
Docker
Designed dual interactive Tableau dashboards for sales performance and customer behavior analysis. Enables stakeholders to identify revenue trends, optimize product strategies, and enhance retention via dynamic KPI monitoring and year-over-year comparisons.
Tableau
Dashboard Design
Built and benchmarked five NLP models (FastText, BERT, DistilBERT, RoBERTa, XLNet) for sentiment classification of product reviews. Designed a full training pipeline with preprocessing, tokenization, and performance evaluation, achieving >90% accuracy on 3,500+ reviews, enabling businesses to automate customer feedback analysis, improve product insights, and enhance customer experience strategies.
Python
PyTorch
Transformers
Flask
Scikit-learn
Built a predictive machine learning model using XGBoost and Stratified K-Fold Cross-Validation to identify customers likely to subscribe to bank term deposits. Addressed class imbalance with SMOTE, optimized feature selection with PCA, and compared multiple models (Logistic Regression, MLP, XGBoost) to maximize predictive performance. Achieved 87% accuracy and 94% AUC, enabling the bank to improve targeted marketing campaigns.
Python
XGBoost
Scikit-learn
Pandas
DataCamp
Ongoing
Validates expertise in AWS solutions.
DataCamp
Ongoing
Covers data pipeline engineering, ETL automation, and modern data workflows in Python.
Analyst Builder
Apr 2025
Covers data pipeline fundamentals, orchestration, and cloud integration using modern tooling.
Code First Girls
Apr 2025
Validates foundational knowledge of SQL, data querying, and relational database design.
DataCamp
Mar 2025
Foundational SQL data engineering concepts including Snowflake, data warehousing, and query optimization.
Udemy
Feb 2025
Comprehensive SQL course covering queries, joins, aggregations, and PostgreSQL-specific features.
Udemy
Nov 2024
Covers core Linux command-line skills, file systems, permissions, and scripting essentials.
I'm always open to discussing new opportunities, collaborations, or just chatting about data and technology. Feel free to reach out through any of the channels below.