I build cloud data pipelines, lakehouse architectures, analytics-ready datasets, and monitoring solutions with Microsoft Fabric, Azure, AWS, Spark, SQL, and Python.
I am currently working at FPT Software as a Data Engineer, with responsibilities spanning data engineering and analytics.
My background is in Software Engineering and backend development. Before specializing in data engineering, I worked with Java, Spring Boot, PostgreSQL, REST APIs, JWT, Android, and frontend technologies. This foundation helps me design data platforms as maintainable software systems, with attention to architecture, reliability, integration, testing, and documentation.
- 🔭 Building data solutions with Microsoft Fabric, Microsoft Azure, AWS, Apache Spark, SQL, and Python
- ⚙️ Working with ETL/ELT, batch processing, incremental loading, orchestration, data quality, and monitoring
- 🏗️ Designing Bronze–Silver–Gold lakehouse architectures
- 🔌 Integrating data from REST APIs, SAP OData, PostgreSQL, CSV, and JSON
- 📊 Preparing analytics-ready datasets for reporting, customer analytics, and downstream analysis
- 🌏 English: Professional working proficiency
- 🇯🇵 Japanese: Basic communication, approximately JLPT N4 level; not certified
A centralized monitoring solution for Microsoft Fabric data pipelines.
- Integrated Microsoft Fabric REST APIs to retrieve pipeline execution metadata
- Designed logging schemas for run IDs, pipeline names, timestamps, execution statuses, and error details
- Parsed and standardized nested JSON responses
- Stored historical execution metadata in Fabric Lakehouse tables
- Implemented validation and error handling for successful, failed, cancelled, and partially completed runs
- Investigated discrepancies between live pipeline statuses and historical logs
Tech Stack:
Microsoft Fabric REST API Fabric Lakehouse Fabric Data Pipeline SQL PySpark JSON
A team-based mock project for subscription analytics across more than 1 million synthetic SaaS records.
- Designed an end-to-end Bronze, Silver, and Gold lakehouse
- Built ingestion workflows for CSV, PostgreSQL, REST APIs, and JSON usage events
- Developed PySpark and Spark SQL transformations for cleansing, standardization, deduplication, joins, and aggregation
- Applied Delta Lake ACID transactions, schema enforcement, and incremental processing
- Produced Gold-layer analytical tables for MRR, churn rate, customer lifetime value, and cohort retention
- Implemented data-quality checks and supported testing, monitoring, troubleshooting, and documentation
Tech Stack:
Python SQL PySpark Spark SQL Azure Databricks ADLS Gen2 Azure Data Factory Apache Airflow Delta Lake
A cloud data platform for ingesting and transforming HR data from SAP OData services.
- Developed Python ingestion jobs to extract SAP HR data and store raw JSON responses in Amazon S3
- Organized datasets into Bronze, Silver, and Gold zones
- Built AWS Glue and PySpark jobs to cleanse, standardize, deduplicate, and integrate HR data
- Registered processed datasets in AWS Glue Data Catalog
- Used Amazon Athena and SQL for validation and downstream analysis
- Implemented reconciliation and data-quality checks for completeness, uniqueness, validity, and consistency
Tech Stack:
Python SQL PySpark Amazon S3 AWS Glue AWS Glue Data Catalog Amazon Athena SAP OData
A batch integration workflow supporting AI-oriented analysis.
- Developed batch jobs to synchronize data from Jira and GitHub APIs
- Standardized source data for downstream processing
- Focused on workflow reliability, data integrity, and cross-system consistency
Tech Stack:
Python REST APIs Jira API GitHub API Batch Processing
A customer analytics workflow for churn prediction and support-ticket sentiment analysis.
- Prepared model-ready datasets for customer churn prediction
- Processed more than 20,000 support tickets
- Applied NLP sentiment analysis with Azure Cognitive Services
- Integrated scikit-learn into the analytics workflow
Tech Stack:
Python scikit-learn Azure Cognitive Services NLP Data Preparation
A full-stack e-commerce platform for Japanese CDs, including a Spring Boot backend and an Android application.
Role: Team Leader & System Architect
- Designed the overall system architecture using Clean Architecture for the backend and MVVM for Android
- Designed PostgreSQL schemas and core business workflows
- Implemented backend security, authentication, authorization, and database features
- Coordinated tasks and technical decisions within the project team
- Implemented role-based access control for Admin, Staff, and User roles
- Built shopping cart, ordering, inventory, staff assignment, and order-management features
- Integrated Firebase Realtime Database for chat
- Integrated Google Maps for store locations and pickup-point selection
- Generated API documentation with SpringDoc and Swagger
Backend:
Spring Boot Spring Security JWT JPA/Hibernate PostgreSQL Firebase Admin SDK Swagger
Android:
Java MVVM Retrofit2 Glide Google Maps API Gradle
🔗 View the JCD Store organization
- Microsoft Certified: Fabric Data Engineer Associate (DP-700)
| 🤝 Pair Extraordinaire | 🦈 Pull Shark ×2 | 🚀 YOLO | ⚡ Quickdraw |
|---|---|---|---|
| Co-authored commits | Merged pull requests | Merged without review | Closed an issue or PR quickly |
“Simplicity is prerequisite for reliability.” — Edsger W. Dijkstra
