Projects and case studies
A collection of work across data pipelines, cloud platforms, ETL, backend APIs, automations and AI workflows.
AWS Crypto ETL Pipeline
End-to-end ETL pipeline on AWS for analyzing crypto prices and Google Trends interest, with raw/silver/gold layers on S3, PySpark transformations in AWS Glue, Step Functions orchestration, Redshift Serverless loading, and QuickSight dashboarding.
Snowflake Hospital Data Platform
Hospital data platform on Snowflake featuring a multi-schema model, an IoT staging-to-clean pipeline, data quality controls, RBAC, GDPR-oriented masking, Time Travel, Zero-Copy Cloning, and clinical analytics queries.
CineData ETL Azure
Parameterized ETL pipeline on Azure Data Factory that transforms a 9,125-film catalog into a Parquet dataset containing 2,726 selected titles, combining Pandas preprocessing, Blob Storage, and Mapping Data Flow.
Breast Cancer Preprocessing Pipeline
Multi-pipeline preprocessing system built with scikit-learn to handle missing values, skewed distributions, categorical variables, feature selection, and dimensionality reduction, producing a final matrix with 569 rows and 43 features.
SQL Banking Customer Analytics
SQL analytics project on a relational banking database that consolidates 359 transactions across 15 customers, calculates balance metrics by account type, and segments the portfolio through CTEs and window functions.
Wikipedia Article Classifier
End-to-end NLP pipeline in PySpark to classify Wikipedia articles into 15 thematic categories, including cleaning of 153,232 raw records, Parquet persistence, 20,000-dimensional TF-IDF feature engineering, Naive Bayes, and qualitative inspection through word clouds.