Shirley Li
About Shirley Li
Shirley Li is a Data Engineer with experience at LinkedIn and Treasure Data. She holds a Master's degree in Data Science and an Advanced Certificate in Financial Econometrics and Data Analysis from Fordham University.
Work at Treasure Data
Shirley Li currently serves as a Data Engineer at Treasure Data, a position she has held since 2023. In this role, she applies her expertise in big data technologies and analytics to support data-driven decision-making processes. Her responsibilities include utilizing advanced data tools and methodologies to enhance the company's data infrastructure and analytics capabilities.
Previous Experience at LinkedIn
Prior to her current role, Shirley Li worked as a Data Engineer at LinkedIn for a period of 8 months in 2022. During her tenure, she contributed to various data engineering projects, leveraging her analytical skills and knowledge of big data toolkits to optimize data workflows and improve data accessibility.
Education and Expertise
Shirley Li holds a Master's degree in Data Science from Fordham University, where she studied from 2019 to 2021. She also earned an Advanced Certificate in Financial Econometrics and Data Analysis during the same period. Additionally, she completed her Bachelor's degree in Economics at Shanghai University of Finance and Economics, where she also pursued a Minor in Mathematics. Her educational background equips her with strong analytical skills and a solid foundation in data analysis.
Technical Skills and Tools
Shirley Li possesses strong technical skills in various data engineering and analytics tools. She is proficient in big data toolkits such as Kafka, Snowflake, and Airflow. Her expertise extends to cloud platforms, including AWS and GCP, where she utilizes services like S3 and Redshift. Additionally, she is experienced in data visualization tools such as Tableau and Power BI, which she employs to generate comprehensive business insights.
Internship Experience
Shirley Li has gained valuable experience through several internships. She worked as a Data Scientist Intern at Amazon for 2 months in 2018 and as a Big Data and AI Intern at PwC for 2 months in the same year. These roles provided her with practical exposure to data science applications and methodologies, further enhancing her analytical capabilities.