Azusa Iikubo

• Initiated, designed, and developed the audit service refactor. The service struggled with data consistency and high latency, which had an impact on business. As a result, success was achieved in reducing latency, increasing service availability, and maintaining data consistency.
• Designed and developed the service split by region. We separated the call chain, service logic, and middleware per region DC. As a result of better service expansion and disaster recovery.
• Designed and developed a pre-authorization process for cross-border orders. Collaborated with stakeholders from different teams and worked with external vendors. As a consequence, we met the government's standards while also improving the user experience.
• Migrated legacy services from Python to Golang, resulting in enhanced codebase maintainability and the removal of old dependencies.
• Introduced unit test flow into the team, developed CICD pipeline flow, and achieved over 85% test coverage in our service repository.
• Collaborated with a varied team of 13 members from over ten different countries, effectively communicating in English.

Technologies used:

• Go
• Python
• Kafka
• MySQL
• Redis
• TiDB
• Docker
• k8s
• gitlab ci
• grpc

Experienced in developing Rakuten point payment systems and data warehousing solutions for Rakuten point users, who account for more than 20 million MAU.

Designed and built a Python-based ETL pipeline architecture for data ingestion, transformation, and analysis. Which was connected with the data warehouse.

Designed and built a data warehouse to capture data from Rakuten point users and enable business intelligence analysis.

Developed new features in Java for Rakuten point payment system, leveraging Rakuten points to drive improved user engagement and income.

Experienced the formation of a new backend team and gave teaching and mentoring to three engineers, resulting in increased team productivity and work quality.

Technologies used:

• Java
• Python
• Hadoop
• Hive
• Airflow
• MySQL
• Docker
• Tableau

Developed a knowledge management system using Java to retrieve documents from cloud services. Natural language processing was used to process documents, and index search capabilities was provided using Solr.

Developed chatbot features for the Japanese market that use natural language processing for word segmentation and indexing.

Technologies used:

• Java
• Solr
• Structs2
• MySQL