South Africa
Backend Software Engineer with experience in architecting and implementing efficient solutions. Skilled in Python, Java, Kotlin, Spring, GCP and AWS services. Demonstrated expertise in improving API response time, optimizing resource allocation, and enhancing system reliability. Proven track record in large-scale API development, data engineering, ML analytics, and full-stack development.
• Spearheaded a select team in developing a state-of-the-art ML-based analytics tool to proactively measure ad creative success for a major advertising agency, serving high-profile clients including Coco-Cola, Adidas, and Nike. • Designed and implemented large-scale data pipelines (DAGs) using Apache Airflow to consolidate data from diverse third-party sources into a data lake for downstream ML processing and precipitating a halving in data processing time and enabling real-time analytics.Developed a highly scalable creative extraction flask application in Python to extract diverse multimedia types from third-party ad-servers (Google, YouTube, Facebook) thus reducing extraction time by 72%. Overcame challenges of handling various media formats and ensuring efficient extraction. • Leveraged Google Cloud Platform (GCP) services, including Cloud Run, BigQuery, and Pub/Sub, to build a scalable and cost-effective data processing infrastructure. Achieved a 28% reduction in infrastructure costs while maintaining high processing capacity. Implemented authentication and authorization mechanisms to ensure secure data access. • Integrated Google APIs (YouTube, DV360, Campaign Manager, Facebook Marketing API) to retrieve data and perform data analysis, thereby providing actionable insights, thus facilitating a 23% QoQ improvement in ad campaign performance and optimization for clients. • Containerized the application using Docker for easy deployment and scalability. Developed RESTful APIs using Flask for efficient communication between microservices.