Years of data engineer experience
Hi, I’m
Youhee Kil
Hilversum
Summary
Results-driven data engineering professional with solid foundation in designing and maintaining scalable data systems. Expertise in developing efficient ETL processes and ensuring data accuracy, contributing to impactful business insights in asset management industry. Known for strong collaborative skills and ability to adapt to dynamic project requirements, delivering reliable and timely solutions.
Overview
3
1
Year of project management experience
4
Certification
Work History
Anthos Fund and Asset Management
Data Engineer
12.2022 - Current
Job overview
- Migrated legacy systems to modern big-data technologies (Microsoft Synapse, Azure Data Factory, Databricks, Power BI), improving performance and scalability while minimizing business disruption.
- Designed and implemented data pipelines to ensure seamless data flow across platforms.
- Automated data validation processes with Great Expectation open source tool to improve consistency and reliability of datasets.
- Developed ETL processes for efficient data extraction, transformation, and loading.
- Collaborated with cross-functional teams to gather data requirements and enhance reporting accuracy.
AMGREEN SOLUTIONS, INC
Project Manager
03.2018 - 04.2019
Job overview
- Data Migration: Supported the IT team in setting up data migration by doing data modeling for digital transformation from CRM Excel to Microsoft Access.
- Data Analysis: Summarized the water usage data on the utility bill, predicted water conservation and presented reports with a dashboard based on the financial evaluation analysis and ROI.
- Leadership, Consultancy: Led the Water Conservation department of 5 team members. Developed and initiated $2 million monetary worth of projects, managed costs, and monitored each project's performance with constant communication with stakeholders, including LADWP So-Cal and MWD.
- Achievement: Improved the department revenue by 30% and achieved the company's highest revenues of the year, earning recognition from upper management.
Education
KU LeuvenLeuven, Belgium
MS from Statistics And Data Science
09.2021
University Overview
- Relevant Courses: Database Management; Data Privacy; Optimization and Numerical Methods; Advanced Nonparametric Statistics and Smoothing; Data Mining; Geographic Information Systems
- Thesis: Estimation of ROC curves in the presence of measurement errors
- Keyword: Measurement Error model, Bernstein polynomial Model, Contaminated Non-parametric Density Estimation, MLE, EM Algorithm
University of California, Los Angeles (UCLA)Los Angeles, CA, USA
BS from Statistics
12.2017
University Overview
- Relevant Coursework: Computation and Optimization for Statistics; Computer Methods for Social Research; Advanced Honors Statistics; Design and Analysis of Experiment
- Project: Improve prediction accuracy of Sugar Streak App users’ blood sugar levels in Type I and Type II diabetes
Skills
- Skilled in data processing with Apache Spark
- Skilled in Python development
- Database querying
- Experience with cloud service platforms (mainly Azure)
- Databricks platform expertise
- Synapse, Azuer Data Factory, Microsoft PowerBI
Certification
- [CFA Institute] Data Science for Investment Professionals Certificate
- [PRI Academy] Understanding ESG
- [Microsoft] Power BI Data Analytics (PL-300/DA-100)
- [Microsoft] Azure Data Engineer (DP-203)
Projects
- Real-Time Twitter Sentiment Analysis: Built an end-to-end Twitter data streaming pipeline for brand sentiment analysis with an NLP pipeline to enhance marketing strategy.
- Dynamic Risk Assessment System: Developed and deployed a Dynamic Risk Assessment System using logistic regression to estimate, predict and monitor customers’ attrition risk using Flask. Also, automated the entire process including the model predictions, F1 score, summary statistics, model diagnostics data (model metrics), and PDF report generation.
- Optimizing Chicago Transportation: Constructed an event pipeline around Kafka to simulate and display the status of Chicago train lines in real-time.
- European Central Bank’s Corporate bonds Purchasing Pattern Analysis: Built automatic web scraper in Python that extracts data from the European Central Bank website, then merges it with data from the Refinitiv database (API) to analyze the purchasing pattern of the corporate bonds and validated hypotheses.