Prathamesh Dakwe

• Designed and implemented reliable and scalable data pipelines using Apache Spark for processing big data, both structured and semi-structured, to enhance efficiency.
• Enhanced data ingestion processes by developing batch processing and real-time data streaming systems using Kafka, similar to message queues, which improved data accessibility and increased data warehousing efficiency by 50%.
• Developed and maintained a real-time monitoring dashboard using Grafana and Power BI to track threats, suspicious activities (such as unauthorized access and data breaches), and anomalies in user behavior. Optimized SQL queries in PostgreSQL to improve dashboard responsiveness and performance, significantly enhancing threat detection efficiency and security incident response times.
• Collaborated on technical designs for Extract-Load-Transform (ELT) pipelines, including High-level Design (HLD), Low-level Design (LLD), and database schema design.
• Implemented containerization of microservices using Docker and Kubernetes, which improved deployment efficiency for the overall data infrastructure.
• Created REST APIs to facilitate seamless interaction between the database and UI dashboard, ensuring accurate responses through endpoint testing.

Possesses Master's degree in Data Science