Career Profile

Masato Nagashima is a Backend Engineer with a specialized focus on Spring Boot, Domain-Driven Design (DDD), and Clean Architecture. With a solid foundation in creating robust and scalable backend systems, Masato excels in developing high-quality, maintainable, and efficient software solutions.

In addition to his backend engineering expertise, Masato has a background as a Data Engineer. His proficiency in SQL, Python, Airflow, data warehouse (DWH) management, and Business Intelligence (BI) design has equipped him with a versatile skill set. This blend of backend and data engineering experience allows him to seamlessly integrate data processing workflows with backend services, ensuring optimal performance and data integrity.

Throughout his career, Masato has demonstrated a strong commitment to best practices in software development, including code quality, testing, and documentation. His ability to bridge the gap between backend engineering and data engineering makes him a valuable asset to any team, capable of handling complex technical challenges and delivering comprehensive, end-to-end solutions.

Experiences

Backend Engineer at Rakuten

April 2024 - Present
Tokyo

Designed and developed a scalable backend architecture for a logistics system. Managed the server-side development of a product with over 1 million monthly active users.

  • Java, Oracle DB
  • Spring Framework, Java, Kubernetes

Backend/Data Engineer at Knowns

May 2022 - March 2024
Tokyo

As a backend engineer, designed and developed backend systems with high scalability and maintainability by adopting DDD and Clean Architecture. As a data engineer, designed and built dwh and data pipelines utilizing Snowflake, RDS, and Redshift.

  • Python, Kotlin, MySQL
  • ChatGPT API, DDD, Clean Architecture, Spring Framework, Snowflake, RDS, Redshift, S3, Machine Learning

Internship at Morgan Stanley

Feb 2023 - Apr 2023
Tokyo

Conducted PoC for machine learning models targeting sell-side products.

  • Python
  • Financial Trading, Unsupervised Learning

Conducted research on a control method for adaptive screw fastening in collaborative robots by introducing deep predictive learning.

  • Python
  • Pytorch, Tensorflow, CUDA, Deep Learning, URX, Math3d

Research

  • Design of 3-dof 2-link inflatable collaborative robot arm with internal drop stitch structure
  • Gangadhara Naga Sai, Masato Nagashima, Hiroki Mori, Seong Young Ah, Hiroki Sato, Ryuma Niiyama, Testuya Ogata
    RSJ 2022

    Skills & Proficiency

    Python

    Java & Kotlin

    Javascript & Typescript