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Hello, my name is Jonathan Park

Jonathan Park

Data Engineer, Data Analyst, and BI Developer

I am a passionate Data Analytics and Business Intelligence Developer with 2+ years of experience translating business needs into data-driven solutions across Finance, Operations, and IT. I also have 4.5+ years of experience conducting quantitative analysis for academic and industry projects. Through deriving data-driven insights and scientific inquiries into human movement and biomechanical data, I developed a strong background in data analysis and a passion for utilizing data to drive decision-making. As a result, I am excited to have transitioned into the field of data engineering, business intelligence, and data analytics so that I can help others understand the data and inform better decision-making for the organization. I am proficient in Python, R, SQL, Power BI, Azure, Tableau and Jupyter Notebooks for data analytics, visualizing data, creating dashboards, statistical analysis, interacting with databases, and implementing machine learning algorithms on large datasets. As a highly analytical and results-driven professional, I am excited to take my unique skills and experience to make a meaningful impact by joining the right company that values data-driven decision-making and innovation. Feel free to connect with me to discuss how we can work together to uncover valuable data-driven insights and solutions.

Certified Tableau Desktop Specialist
Microsoft Certified - Power BI Data Analyst Associate
Analytical
Leadership
Team Work
Hard Working

Skills

Power BI
Power BI

Experienced in designing interactive dashboards, building data models, writing DAX measures, and creating paginated reports. Skilled in data transformation using Power Query and integrating multiple data sources including Excel, SQL databases, and cloud services.

Microsoft Azure
Microsoft Azure

Experienced with Azure Data Factory for building ETL pipelines, Azure SQL Database for relational data storage, and Azure Synapse for analytics. Knowledge of data integration, monitoring, and orchestration in a cloud environment.

Power Automate
Power Automate

Skilled in automating workflows across Microsoft 365 and Power BI. Experience includes building scheduled and event-based flows to streamline business processes and reduce manual effort.

SQL
SQL

Skilled in writing complex queries, stored procedures, and window functions for data transformation and analysis. Experience includes SQL Server, Azure SQL, and optimizing queries for performance and scalability.

Python
Python

Proficient in data cleaning, data analysis, creating data visualizations, implementing, statistical analysis, and implementing machine learning algorithms. Libraries include: pandas, numpy, matplotlib, seaborn, and scikit-learn.

Matlab
Matlab

Utilized as the main language for implementing digital signal processing techniques on biomechanical data and various analytical techniques, such as: cross-correlation, and discrete Fourier transform, and machine learning algorithms.

Azure Databricks
Azure Databricks

Experienced in developing and testing scalable data pipelines using Azure Databricks notebooks.

Cloud Computing
Cloud Computing

Worked with AWS (S3, EC2), PySpark, Hadoop for wrangling and analyzing a dataset with ~260 million rows of data.

R
R

Implemented hypothesis testing and statistical modeling techniques for thesis and research projects.

Tableau
Tableau

Skilled in creating data visualizations, creating interactive dashboards, and analyzing data sets to provide insights for various business units.

Git
Git

Experienced with version control or git-based development. Mostly, use Github.

Jupyter Notebook/JupyterLab
Jupyter Notebook/JupyterLab

Proficient in creating reproducible notebooks and workflows for conducting interactive data analysis and visualization through leveraging Python.

Experiences

1
Data Engineer and Power BI Developer (Contractor)
Procor Limited

Apr 2023 - May 2025, Oakville, ON

Responsibilities:
  • Developed 8 Power BI reports and maintained 13+ Power BI and paginated reports for Finance, Operations, HR, and IT teams, delivering enhancements, resolving issues, and fulfilling ad-hoc requests for executive and operational reporting.
  • Engineered a SQL stored procedure to align materials-installed data with ERP vouchers using window functions, supporting Finance in accurately reporting $10M+ in WIP material costs.
  • Automated a WIP Excel reporting process by developing a Power BI report, semantic model, and Power Automate workflow, improving precision of month-end accruals and saving 12+ hours of manual effort monthly.
  • Migrated a legacy ERP report by replicating complex business logic in Azure Data Factory and building a Power BI semantic model (data modeling) and paginated report, reducing month-end system load by 70-90% and cutting report runtime to under 1 minute.
  • Built and maintained relational database objects and semantic models to support Power BI reporting.
  • Managed data integration from 5+ sources into a centralized data warehouse using Azure Data Factory.
  • Developed a Power BI report to visualize ETL metadata and lineage, cutting 80% of manual effort previously required to navigate the low-code ETL interface for data lineage tracing and migration.
  • Resolved 94+ help desk tickets with an average turnaround of ~7 hours, reducing backlog and addressing stakeholder support across the organization.
  • Managed Power BI Service refresh schedules, access provisioning, and usage data to ensure reliable delivery of business-critical reports.
Sport Biomechanist (Contractor)
Canadian Sport Institute Ontario

Feb 2021 - Mar 2022, Scarborough, ON

Responsibilities:
  • Calculated various metrics for cross-functional team member by conducting biomechanical time-series data analysis and world para-athletics points calculations.
2
3
Biomechanics Consultant
S-E-A Limited

Jan 2020 - Nov 2020, Columbus, OH, USA

Responsibilities:
  • Achieved company-wide, superstar status for collaboratively supporting litigation matters by analyzing case evidence, researching scientific literature, reviewing industry best practices, preparing reports, liaising with internal staff, and preparing presentations on evidence-based findings to both technical and non-technical stakeholders.
  • Prepared documentation, developed testing protocols, and collaborated with technical staff to evaluate a variety of equipment, while tracking budget and expenditures.
Research Assistant (Contractor)
Canadian Sport Institute Ontario

Dec 2018 - May 2019, Scarborough, ON

Responsibilities:
  • Constructed an interactive dashboard for cross-functional team members and automated the process of collecting, processing, analyzing, and visualizing time-series data, thereby providing stakeholders with feedback on key performance metrics within seconds.
  • Successfully calculated key metrics from IMUs by conducting time-series data cleaning, analysis, and critically evaluating the calculations and interpretation of the metrics with scientific literature.
  • Delivered a presentation on project analysis and findings to CSIO staff, submitted a conference abstract, composed a year-end stakeholder report, and authored a comprehensive manual for the dashboard to facilitate knowledge transfer.
4
5
Graduate Researcher and Teaching Assistant
University of Waterloo

Sep 2015 - Sep 2018, Waterloo, ON

Responsibilities:
  • Independently organized the study design, evaluated results, and summarized thesis findings with 88 static visualizations (e.g., graphs, diagrams, tables).
  • Presented at international conferences, prepared six conference abstracts, and co-authored a peer-reviewed publication.
  • Implemented various algorithms (e.g., digital filtering, residual analysis, cross-correlation, regression, interpolation) on time-series data and calculated 15 dependent variables for statistical analysis in R.
  • Presented six bi-weekly tutorials on research methods, statistical techniques, and study design concepts for 40 undergraduate students.

Education

BrainStation
2022
Data Science Diploma
Percentage Scale: 93.9 out of 100
Taken Courses
  • A full-time project-based Diploma program in Data Science
  • Bixi Project 1 (MySQL, SQL)
  • Bixi Project 2 (Tableau)
  • Stats and Public Health Part 1 (Python - numpy, pandas, matplotlib, seaborn)
  • Stats and Public Health Part 2 (Python - statsmodels, scipy)
  • NLP with Hotel Reviews Part 1 (Python - sklearn)
  • NLP with Hotel Reviews Part 2 (Python - sklearn)
  • Big Data Wrangling with Google Books Ngrams (AWS S3, AWS EC2, Hadoop, PySpark)
  • Capstone - Sentiment Analysis and Topic Modeling on e-commerce App Store Reviews (Python)
University of Waterloo
2018
M.Sc. in Kinesiology (Biomechanics)
Publications
University of Waterloo
2015
B.Sc. in Honours Kinesiology, Dean's Honours List
Publications
Extracurricular Activities
  • Volunteer teaching assistant for human anatomy lab tutorials.
  • Kinesiology lab days instructor for ergonomic lab demonstrations.
  • Well-Fit volunteer assistant for patients undergoing cancer treatments with their exercise regimen.
  • Student mentor for first-year students.

Projects

YouTube Data API Project - CBC News Marketplace
Lead Developer Mar 2023

Retrieved data on 300+ CBC News Marketplace videos using the Youtube Data API, and performed analysis on video titles, views, likes, and comments.

hobby python api
Star
NLP Project on e-Commerce App Store Reviews
Lead Developer Feb 2022 - Apr 2022

Applied various text-preprocessing techniques to ~450,000 user reviews, including regular expression, text normalization, and language detection. Contributed to the development of automated solutions for analyzing customer reviews, which could potentially improve the feedback utilization process for app developers.

capstone machine-learning python
Star
Data and Visual Analytics on Bixi Data
Coursework Jan 2022

Generated 15 queries, four calculated fields, ten data visualizations, and an interactive reporting dashboard to gain insights into service usage and then developed recommendations for improvements.

coursework sql mysql tableau
Master's Thesis Project
Lead Researcher Sep 2018

Implemented digital signal processing techniques, and various analytical techniques on quantitiative (i.e., biomechanical data) and qualitatitve (e.g., questionnaire) data using Matlab and R.

academic biomechanics kinematics electromyography R matlab
Details
Previous Research and Industry Biomechanics Projects
Lead and Assistant Researcher

Previous work completed for research and industry biomechanics research projects. Techniques used include digital filtering, residual analysis, data interpolation, cross-correlation, statistical analysis, kinematic analysis, and machine learning.

professional academic matlab R python machine-learning v3d
Details

Accomplishments

Tableau Desktop Specialist Certification
Tableau Feb 2023

Earners of the Tableau Desktop Specialist title use their foundational knowledge of Tableau Desktop and data analytics to solve problems. They have demonstrated understanding of Tableau core concepts and terminology. Desktop Specialists are able to connect to, prepare, explore and analyze data, and share their insights.

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Accenture Data Analytics and Visualization Virtual Experience Program
Forage Dec 2022

This virtual experience helped me understand data basics, such as data cleaning, modeling, visualization and storytelling through Microsoft Excel and Powerpoint. The skills gained include: understanding the business problem, data cleaning & modeling, data analysis, visualization, and public speaking.

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R Programming Course
Coursera Jul 2021

The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.

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The Data Scientist’s Toolbox
Coursera Jul 2021

The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

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Machine Learning
Coursera Nov 2019

This course provides a broad introduction to machine learning, data mining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).

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