Available for Hire
Hi, I'm Stanley Agorchukwu
Data Engineer building scalable systems for real-time insights and robust data governance.
Data Engineer building scalable systems for real-time insights and robust data governance.
Python
SQL/dbt
Spark
Airflow
AWS
Docker
Problem: The lack of a centralized, automated data pipeline for eyewear vendors resulted in fragmented product information and pricing inconsistencies, hindering the ability to provide patients with real-time, accurate comparisons.
Problem: Scaling security analytics to process 10M+ daily events while maintaining sub-5-minute latency for fraud detection requires a distributed architecture to overcome the memory constraints and throughput limitations of traditional data systems.
Problem: Ziko Logistics faced operational bottlenecks due to disparate data silos (IoT, ERP, CRM), exponential data volume/velocity, and inconsistent data quality that delayed critical decision-making. I engineered a scalable, automated ETL framework using Python and Windows Task Scheduler to ingest real-time API data into Azure Data Lake Gen 2, ensuring a centralized, high-quality "single source of truth" for predictive analytics