Here's some information that can help you to know about me, let's go!

TLDR; Check out this pdf or image versions of my CV.

• 01/2022 -> present: Data Engineer at MoMo (M_service). From MoMo Talents Program.

• 2018 -> 05/2022: Student at University of Science - Viet Nam National University, Ho Chi Minh City. Faculty of Information Technology. Data Science major in the field of Computer Science. GPA: 8.5

• Sep 13, 2023 -> MEP: A Comprehensive Medicines Extraction System on Prescriptions in ICCCI 2023: Computational Collective Intelligence.
• Sep 21, 2022 -> Medical Prescription Recognition Using Heuristic Clustering and Similarity Search in ICCCI 2022: Computational Collective Intelligence.

• Agile / Scrum concept
• Programming Languages (C/C++, Java, Kotlin, Python, SQL,...)
• MS SQL Server / Oracle OCI / Bigquery / Vertica / Trino
• Open Table Format (Delta Lake / Apache Iceberg)
• Command Line (with or without Linux/Unix system)
• Git and Version Control
• CI / CD
• Shell / Linux
• Docker
• Kubernetes
• ETL / ELT
• Spark Application
• Data modeling
• Data Observability / Data Quality / Data Catalog / Data Security
• Data Governance
• Google Cloud Platform (Bigquery / PubSub / Dataproc / GKE / GCS / Cloud Functions / Resource monitoring / Looker / GCP gRPC API)
• Oracle APEX
• Scikit-learn
• Machine Learning Algorithms
• Generative AI
• MS Office
• Kubectl / Helm / Skaffold

• Great Expectations
• dbt
• Airflow
• Datahub
• Oracle APEX
• Trino
• Apache Spark
• Apache Ranger
• Data Visualization Tools
• Machine Learning Tools
• LangChain

• great-expectations/great_expectations#6145
• vertica/dbt-vertica#32
• oracle/dbt-oracle#31

• Golden Record - Process to achieve high-value Data Mart at MoMo
  Build tools and services on top of open-source projects to control the data model's quality, freshness, and extensionality. Golden Record currently serves many dataflows such as events and transactions of the MoMo Super App.
  Used: dbt, Great Expectations, Airflow, Gitlab, Kubernetes, Oracle OCI, and Oracle APEX.

• Cost Optimization - Reduce cost on GCP
  Support other teams to optimize queries: move services, ETL, and ELT to on-premise Kubernetes. Try to shift from Bigquery to Vertica. Manage GCP resources for each team in MoMo by the divide-and-conquer principle.
  Conclusion: 40% cost saved without any stuck workload.
  Fluent in: Bigquery, Vertica, Kubernetes, Oracle APEX, GCP gRPC API.

• Data Observability - Data Governance
  Just a project which helps end-user monitor five pillars of data: Freshness, Volume, Quality, Schema, and Lineage. This project aims to reduce the workload of the data-platform team in responsiveness to data for both info and incident.
  Fluent in: Datahub, dbt, Great Expectations, Airflow.

• Data Lakehouse
  Collaborate with the team to build a lakehouse solution to reduce the cost of all workloads at Momo. Trino/Spark run on GKE as a query engine to process large batch data stored in GCS. Reduce up to 70% cost per workload thanks to Spot instance without any data SLA.
  Fluent in: Trino, Spark, GKE, GCS, Bigquery Storage, dbt, Airflow, Apache Ranger, Delta Lake, Apache Iceberg

• Citizens problems detection
  Deep Learning @ AI4VN

• Predict Covid19
  Machine Learning/Data Visualization/Data Analyst

• Plant Pathology
  Deep Learning

• Hospital Inpatient Discharges
  Data Visualization/Data Analyst

• Image Color Compression using Kmeans
  Image Processing

• Image Transformation
  Image Processing/Image Transformation

• Data Preprocessing Toolkits from scratch (python)
  Data Processing

There are a lot of badges (with AI, Machine Learning, Deep Learning, and Data Scientist) I have reached from that base on Google Cloud Platform.

Let's check out my Qwiklabs Public Profile.

• Linkedin
• Facebook
• Email: hvduy37@gmail.com

Github Page: viplazylmht.github.io