Technical Achievements:

• Led the architecture and implementation of a scalable data platform (a.k.a DataPortal) for FairPrice Group (FPG) using Google Cloud Platform (GCP) services.
• Led the development of in-house solutions for the data team at FPG.
• Led the customization and optimization of Data open-source solutions to align with the specific requirements of FPG.
• Worked with vendors to validate the solution for the data team department, including assessing capacity requirements and ensuring the solution fit within budget constraints

Tech Stacks:

• GCP: Bigquery, Cloud Composer, GKE, GCS, Cloud Run, Cloud Function, CloudSQL, Vertex AI.
• Programming Languages: Python, SQL, Javascript (ReactJS).
• Others: Apache Superset, Apache Flink, Datahub, Apache Beam, Apache Spark, Debezium, Kafka..

Business and Operation Impacts:

• Led a data team (2 headcounts in Singapore, and 2 headcounts in China) in migrating the data warehouse during the platform transition from an on-premise solution to Alibaba Cloud, ensuring zero downtime for all downstream reports across six countries.
• Led key components (First mile, Sortation, Last mile) in the Logistic Data Product (Eagle), enabling the operations team to achieve a 25-30% reduction in logistics costs.

Tech Achievements:

• Architected and constructed end-to-end core data pipelines for a new BIG Logistics Data Warehouse utilizing technologies such as Kafka, Hadoop, Hive, MapReduce, Spark, and Flink in the same six countries.
• Architected and built data pipelines with a Lambda architecture (Batch + Real-time) for core modules in Logistics Data Products, both internal and external, using Flink, Hive, Hadoop, HBase, MySQL (Sharding), and Hologres, again in the same six countries.

Business and Operation Impacts:

• Enabled data-driven operations across six countries, resulting in improved decision-making and operational efficiency for Lazada Logistics.
• Reduced manpower costs for BI and Operations teams across six countries by building centralized data models, ensuring data consistency and quality.
• Reduced manpower costs for Operations teams and 3PL Partners by enabling end-to-end data for the data product (3PL portal) that serves all 3PL companies partnering with Lazada.

Technical Achievements:

• Managed a 300TB+ Hive Data Warehouse (MaxCompute) for Lazada Logistics in six countries (Singapore, Indonesia, Malaysia, Thailand, Philippines, and Vietnam).
• Built automation tools for internal processes to reduce manpower costs.

Business Impacts:

• Led the architecture and implementation of the data processing side for the second AI product (Addy version 1), enabling the company to analyze social media data and generate actionable insights. This innovation significantly contributed to securing additional investment by demonstrating the company's advanced analytical capabilities and growth potential.

Tech Achievements:

• Designed and developed a scalable data processing pipeline using AWS cloud services for Addy, capable of scaling out to run up to a hundred end-to-end data pipelines with Machine Learning models. This included the orchestration of data ingestion, preprocessing, feature engineering, model training, validation, and deployment
• Worked with the Data Science team to deploy and scale machine learning models in the AWS cloud.
• Mentored junior team members in using Apache Spark and solving complex technical problems.

Business Impacts:

• Led the development of the company's first AI data product (TenPoint7 Cloud), significantly enhancing the ability to present and sell ideas to both investors and clients, including those in marketing and non-profit sectors in the U.S.
• Provided technical support to the data consulting team, improving the delivery of results and overall client satisfaction.

Tech Achievements:

• Implemented data lake and pipeline solutions for clients, utilizing tools such as Airflow, EMR, S3, ECS, Lambda, and API Gateway.
• Built scalable crawlers and ETL tools using ECS(Fargate), S3, Docker, Python, DynamoDB, SQS, SNS, and Athena. ( capable of scaling out to support thousands of data points simultaneously)

Tech Achievements:

• Optimized Miki's Content Management System (CMS) and tuned databases for performance.
• Created and modified APIs to enhance functionality for mobile applications.
• Integrated Miki's systems with TIKI's existing infrastructure.
• Implemented Continuous Integration/Continuous Deployment (CI/CD) pipelines.
• Migrated Miki's system to a cloud-based architecture (AWS) and adopted microservices (Docker).

Building a Software-as-a-Service (SaaS) business intelligence platform for retail. The SaaS solution includes features such as optimal order management, sales trend analysis, and sales forecasting.

Business Impacts:

• Developed a Proof of Concept (PoC) to showcase the platform's value to investors.

Tech Achievements:

• Led the backend development of the SaaS platform.

Tech Achievements:

• Developed a scalable system using Queue Architecture (RabbitMQ) capable of crawling and processing data from multiple sources, handling up to millions of records.

Creating and modifying functions, web services, and modules in Odoo (former OpenERP)