Liang

Intro

I am a Data Engineer experienced in cloud-based big data solutions, including data warehousing, data quality, data modeling, data ingestion, data transformation, APIs, and cloud computing. I worked with SQL/NoSQL databases, ETL tools (SSIS, Matillion), orchestration tools (Apache Airflow), cloud data warehouses (BigQuery, RedShift, Snowflake), data processing framework (PySpark), infrastructure tools (Terraform), data visualization tools (Tableau, SiSense). I love to engage in cross-team environments and learn new technologies, understand business requirements, and deliver high-quality data products to add value to the business. If you would like to contact me, reach out to me here or through my LinkedIn profile

• LinkedIn
• GitHub

Education

University of Toronto
Bachelor of Science, Computer Science & Statistics Double Major
GPA: 3.97/4.00
Sep 2019 - Apr 2023 (Expected)

University of Florida
Master of Engineering, Chemical Engineering Major
GPA: 3.78/4.00
Aug 2012 - May 2014

Lanzhou University
Bachelor of Science, Chemistry Major
GPA: 4.21/5.00
2008 Sep - June 2012

Work

Database Assistant
University of Toronto, Department of Computer Science
Oct 2022 - Present
Skills: SQL; Microsoft Access; Database design principles; Data analysis and management; Pivoting tables and data validation etc.; Programming with programming languages such as VBA and Python; Automation of tasks like tables generation and offer letter generation; Collaboration and communication; Troubleshooting and problem-solving

• Helped manage the admissions database for the University of Toronto Computer Science Department Graduate Program.
• Designed and implemented new features to replace manually data ingestion and data transformation that reduce errors by 50%
• Developed a series of customized reports to help the admissions team track and analyze applicant data more efficiently

Data Engineer, Business Intelligence
Ecobee Inc.
May 2021 - Apr 2022
Skills: Relational database management; High-volume data ingestion from various sources; Data modeling; Data pipeline architecture (design/deployment/matainance); Large-scale data lakes and data warehouses construction; Automation of workflow; Data validation and visualization

• Ingested high volume of data from a variety of data sources such as MySQL, PostgreSQL, MongoDB, JSON files, CSV files, Salesforce on Cloud Storage, Netsuite etc.
• Participated in data modeling such as Ecobee Sells modeling and subscription modeling.
• Developed, deployed and maintained resilient data ingestion and transformation pipelines with a variety of tools such as Matillion, Cloud Functions on Python, SQL stored Procedures on GCP BigQuery.
• Built large-scale data lake and data warehouses on BigQuery that adhere to Kimball's dimensional data modeling principles
• Utilized Airflow to schedule and monitor all ELT tasks, and resolved Airflow job failures in a timely manner to avoid substantial impact on business operations.
• Administered the Team's Google Cloud Platform with Terraform
• Developed data visualizations on Tableau and SiSence for data reporting

Data Analyst Trainee
Easy Career Group
Dec 2019 - Feb 2020

• Queried large volumes of data from AWS Cloud SQL database, created weekly and monthly reports to monitor over 1000 products' sales performance by each store location
• Designed and developed inventory reports to track and monitor product availability at each store; provided solid data to support business decisions on replenishment strategies
• Automated the monitoring reporting process for a Credit Limit Increase marketing campaign and created a Tableau Dashboard to evaluate post-campaign performance

Data Analyst, Supply and Material Planning
Wuhu Longtai Steel Structure Equipment Manufacturing Co., Ltd
Mar 2016 - July 2018

• Utilized Excel and VBA to manipulate data and designed new analytical tools to monitor and forecast sales, shortening reporting time from one day to 2 hours
• Maintained positive relationship with 5 national venders and worked closely with a team of 4 in product allocation, resulting in an average of 95% product delivery rate

projects

Machine Learning Project - Online Education Assessment

Software Design Project - Calendar Android App

• Utilized Java to develop a Calendar application on Android system;
• Designed the UI for users to log in and implemented advanced features such as sharing with friends and searching for appointments;
• Created unit tests and mocked applications to validate developed functionality;
• Ensured accurate written documents on GitHub regarding code changes, feature improvements and debugging results

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PostgreSQL Database Project - Ride-sharing Company


• Conducted data modeling for analysis purposes on a ride-sharing company's dataset;
• Developed complex, stand-alone SQL queries and integrated them into a Python program using psycopg2;
• Designed comprehensive datasets, including scenarios and edge cases, to thoroughly test SQL queries for accuracy and reliability

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MIPS Assembly Project - Doodle Jump Game Simulation


• Completed a comprehensive implementation of the Doodle Jump mobile game using MIPS assembly language;
• Utilized a simulated environment within MARS to test the implementation;
• Accomplished a set of objectives, including creating animations, implementing movement controls, developing a random platform generator;
• Added game features such as a scoreboard and dynamic increase in difficulty, as well as additional features such as power-ups and fancier graphics

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Time Series Project - CO₂ Concentration Time-series Data Analysis


• Conducted exploratory analysis of CO₂ concentration time-series data from Mauna Loa Observatory, Hawaii;
• Applied transformations to convert the data into a stationary process and proposed at least two ARIMA or SARIMA models;
• Estimated model parameters, performed diagnostics, and selected the best model based on selection criteria;
• Forecasted the data into the future ten-time periods with 95% prediction intervals and performed periodogram analysis to identify the first three predominant periods, obtaining confidence intervals and interpreting the findings.

courses

Computer Science Courses:
Introduction to Databases
Neural Nets and Deep Learning
Data Structures & Analysis
Numerical Methods
Software Design
Software Test & Verification
Software Tools and Systems Programming
Computer Organization
Intro Machine Learning
Introduction to Computer Science
Introduction to the Theory of Computation
Mathematical Expression and Reasoning for Computer Science

Statistics Courses:
Probabilty & Statistics
Methods of Data Analysis
Methods of Applied Statistics
Methods for Multivariate Data
Time Series Analysis
Design and Analysis of Experiments
Theory of Statistical Practice
Probability

Math Courses:
Linear Algebra
Advanced Calculus

Economics Courses:
Principles of Microeconomics
Principles of Macroeconomics

About

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i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';