Vincent Lau

Implemented ETL operations in a high-volume data environment, reducing data load time by 25%, responsible 100% of designing and documenting 30+ table schemas and all data quality across product verticals and related business areas.

• Communicated with business departments to understand needs in order to build 10+ data pipelines for analyzing technical issues.
• Formulated efficient data pipelines with Google Cloud Dataflow, facilitating quicker data transformation.
• Used Airflow to build ETL solutions that helped improve conversion rates by 16%.
• Developed and optimized complex SQL queries and designed index, improving query speed by 35%.

KEY TECHNOLOGIES: ELT, SQL, Python, Airflow, Kettle, PowerBI, Azure, Script

Led a team of 8 data engineers in designing and implementing scalable data solutions to support various business functions. Discussed customer needs and documented their requirements for projects, ensuring all data solutions met customer expectations.

• Created data mapping documentation based on customer requirements.
• Designed and implemented scalable data models, increasing data query performance by 35%.
• Optimized existing databases, resulting in a 20% reduction in storage costs and improved system performance utilizing DB2.
• Used DB2 to write stored procedures to extract and transform data, enhancing data processing accuracy and efficiency.
• Designed and optimized ETL pipelines using Python and SQL, reducing data processing time by 30%.
• Automated data loading and reporting processes, decreasing manual effort by 80% and improving accuracy using Shell scripting.
• Led efforts to migrate local data infrastructure to Azure cloud services, enhancing scalability and reducing maintenance costs.

KEY TECHNOLOGIES: DB2, SQL server, SQL, Linux, Shell, Kettle, Tableau, AWS, Python, Logistic Regression, Linear Regression

• Supported the development of ETL processes while updating the data mapping documentation as needed.
• Mastered ETL processes with Kettle and SQL, optimizing data flow from source databases to MySQL central data warehouse.
• Provided solutions and data support to on-site implementation engineers.

KEY TECHNOLOGIES: MySQL, Oracle, SQL, Kettle, Tableau, Java

Led a team of 3 interns in developing and optimizing data engineering solutions, providing mentorship and guidance to new team members, fostering their professional growth and development in data engineering practices.

• Applied agile development to enhance project delivery efficiency, resulting in a 20% increase in productivity.
• Collaborated with cross-functional teams to identify and address data needs, resulting in improved data quality and accessibility.
• Utilized MySQL database for data storage and management, ensuring data integrity and reliability.
• Developed and maintained ETL processes, enhancing data extraction and transformation accuracy by 20% using Kettle.
• Implemented Airflow for scheduling and orchestrating complex data workflows, improving data processing automation.
• Reduced database downtime by 30% by implementing a robust backup and recovery system utilizing MySQL and Azure services.

KEY TECHNOLOGIES: MySQL, Oracle, SQL, Kettle, Tableau, Java