Data Engineer with experience in data warehouse development, ETL, cloud migration, and data pipeline implementation. Skilled in Python, C#, C++, NodeJS, SQL, AWS, Terraform, Airflow, Spark, PySpark, Power BI, and machine…
Data Engineer with experience in data warehouse development, ETL, cloud migration, and data pipeline implementation. Skilled in Python, C#, C++, NodeJS, SQL, AWS, Terraform, Airflow, Spark, PySpark, Power BI, and machine learning, with experience across data engineering and analytics roles.
• Led and participated in the development of the data warehouse project for mobile notifications pushing and emails, using
PostgresRDS, AWS Lambda, SalesForce Journey, and Braze Canvas. – HK Disneyland
• Designed and implemented a data ingestion pipeline for ingesting manifest and CSV files from on-premise to PostgresRDS, using AWS
API Gateways, AWS Lambda, AWS S3, and NodeJS as the programming language. – HK Disneyland
• Continuous Integration/Deployment Pipeline Integration, pull requests, code reviews, load/stress testing with the use of Jenkins, Git Hook
Alantis and Terraform. – HK Disneyland
• Conducted User Acceptance Testing (UAT) to validate the functionality and performance of the developed solutions. – HK Disneyland
• Designed and implemented part of ETL process in a large-scale cloud migration project (cloud migration from on-premises Oracle to AWS Redshift). AWS Glue with PySpark was used to transform and load data, which was spooled by SAS and originally loaded to Oracle by SQL Loader, from S3 to Redshifts. EventBridge and Lambda were also used for flow orchestration purposes. – PCCW
• Deployed necessary infrastructures with the use of AWS CloudFormation and Parameter store. Set up Postgres RDS on EC2 for batch transaction monitoring. – PCCW
• Implemented envelope encryption practice for data encryption key and database permission control for data security, using Redshift, AWS KMS, and SecretsManager. – PCCW
• Participated in the development of ETL process development using Apache Airflow (MWAA). – PCCW
• Continuous Integration/Deployment Pipeline Integration, pull requests, code reviews, with the use of AWS CodePipline, and CodeCommit. – PCCW
Led and participated in the development of the data warehouse project for mobile notifications pushing and emails, using PostgresRDS, AWS Lambda, SalesForce Journey, and Braze Canvas.
Designed and implemented a data ingestion pipeline for ingesting manifest and CSV files from on-premise to PostgresRDS, using AWS API Gateways, AWS Lambda, AWS S3, and NodeJS as the programming language.
Performed continuous integration/deployment pipeline integration, pull requests, code reviews, and load/stress testing with Jenkins, Git Hook Alantis, and Terraform.
Conducted User Acceptance Testing (UAT) to validate the functionality and performance of the developed solutions.
Designed and implemented part of ETL process in a large-scale cloud migration project from on-premises Oracle to AWS Redshift.
Used AWS Glue with PySpark to transform and load data from S3 to Redshift.
Used EventBridge and Lambda for flow orchestration purposes.
Deployed necessary infrastructures with AWS CloudFormation and Parameter store.
Set up Postgres RDS on EC2 for batch transaction monitoring.
Implemented envelope encryption practice for data encryption key and database permission control for data security using Redshift, AWS KMS, and SecretsManager.
Participated in the development of ETL process development using Apache Airflow (MWAA).
Performed continuous integration/deployment pipeline integration, pull requests, and code reviews with AWS CodePipeline and CodeCommit.
Maintained and optimized the data pipeline from various data sources to Power BI dashboards, ensuring the accuracy and integrity of data.
Created and edited Power BI dashboards reporting to the heads of underwriting teams.
Transformed manual Excel handling to Python scripting, resulting in increased efficiency and reduced human errors.
Responsible for data cleansing and data mining of the Employee Benefit data, which is used for machine learning purposes.
Participated in a machine learning project utilizing XGBoost and CATBoost algorithms to conduct a cross-selling campaign.
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