Mathematics and Applied Mathematics graduate with specialized certifications in Data Engineering, Machine Learning, and Artificial Intelligence. Skilled in designing scalable ETL/ELT pipelines, data warehousing, and building ML-ready datasets. Experienced with cloud platforms (AWS, Azure) and modern data stack tools including Apache Spark, Airflow, and dbt. Passionate about solving complex data problems, optimizing query performance, and building robust data infrastructure that powers business intelligence and AI applications.
Currently available for opportunities in Data Engineering, SQL Development, and AI/ML Engineering.
Automated ETL pipeline for real-time weather data ingestion, transformation, and dashboard visualization. Optimized for 50% faster query performance.
Real-time streaming analytics platform processing IoT sensor data with anomaly detection and alerting within 5 seconds of event occurrence.
End-to-end data pipeline for energy consumption forecasting using statistical models and time-series analysis with interactive dashboards.
LLM-powered assistant for data engineering education with retrieval-augmented generation and multilingual search capabilities.
AI-powered Bible study assistant with multilingual search, progress tracking, and natural language understanding across multiple translations.
Performance measurement and optimization of ETL pipelines using statistical methods to analyze throughput, latency, and resource utilization.
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