Data Engineer

Conducted data research and quantitative analysis to evaluate educational outcomes for girls’ scholarship programs; processed 50K student records across 8 data sources, reducing reporting errors by 30%, strengthened monitoring, reporting, and decision making. Built concise reports and interactive visuals using Python, SQL, and BI tools; delivered clear, actionable, and strategic insights for program leads and donors that effectively guided resource allocation, outreach prioritization, and impactful communications.

Designed and developed scalable AWS-based data architecture using Python, SQL, Snowflake, and Databricks to support large-scale data warehouses and datamarts, enabling robust analytics and BI reporting, which improved data processing efficiency by 18%. Implemented ETL processes and optimized PL/SQL queries, reducing average query runtime from 2.5s to 1.7s (32% faster). Developed and implemented data acquisition for customer records using data ingestion and PyTorch, improving accuracy by 25%. Integrated AWS SageMaker with DynamoDB and Lambda to build machine learning models, decreasing model training by 6 hours. Built AI-driven data pipelines by implementing root cause analysis using large language models (LLMs), focusing on deep learning optimization and model alignment; achieved 99% model accuracy in anomaly detection pipeline by reducing bottlenecks.

Pioneered cloud infrastructure on Azure Data Factory, boosting data processing by 20%, low-code integration for client solutions. Managed project documentation for apps in agile environment and performed real time data visualization using PowerBI dashboards.

Designed and developed data-driven solutions and segmentation models using statistics, classification, and data mining techniques with scikit-learn and numpy on more than 10k records; conducted evaluation using metrics like confusion matrix and ROC curve. Leveraged data mining techniques on existing market data, uncovering key product satisfaction patterns; communicated findings to fix the three biggest causes of product dissatisfaction and user experience, improving recruitment outcomes by 15%.