Oleksii

Oleksii Nebrat

14.05.2002
[открыть контакты](см. выше в блоке «контактная информация») | [открыть контакты](см. выше в блоке «контактная информация»)

https://leetcode.com/u/sasm-doppleganger/

Professional Summary
Data-focused professional with hands-on experience building CGS-based data lake/ware-houses
and automating ETL/ELT pipelines using Python, dbt, SQL and Alteryx. Strong background in SQL
optimization and data modeling with enterprise experience at PwC.

Skills

• Data Engineering: Data Modeling, Indexing, Query Optimization, Data Orchestration,
Data Lake/Data Warehouse Understanding, Data Normalization, SCD
• ETL / Data Processing: dbt, Alteryx, pandas
• Databases: BigQUERY, PostgreSQL, MySQL
• Programming & Automation: Python, VBA, Google Apps Script
• Cloud & Infrastructure: GCS
• Data Analysis & Visualization: Google Data Studio, Power BI (DAX), Tableau, Excel
• Process Automation: Data pipeline optimization, script migration, task automation
• Soft Skills: Problem-solving, analytical thinking, teamwork, attention to detail
• Version Control & DevOps: Git, GitHub, CI/CD basics

Work Experience

Junior Data Analyst
PwC Service Delivery Center |18.11.2024 – 8.11.2025

• Designed and optimized 15+ recurring workflows and automated data pipelines using
Alteryx and VBA, reducing manual processing time by 60%.
• Processed datasets of 500K+ rows and improved data validation accuracy by 25%,
increasing reliability across reporting workflows.
• Implemented structured data transformations and validation logic within automated
pipelines to ensure consistency across reporting datasets.
• Migrated Google Scripts to VBA and Excel Online, ensuring seamless transition and
improved functionality

Education

Bachelor’s Degree in Cybersecurity
National Aviation University | September 2019 – May 2023
Certifications & Courses

• Data Analyst Course – Udemy
• Data Engineering Course – Udemy
• Data Warehouse Course – Udemy

Projects

• Rental Market Lakehouse Platform (Google Cloud)
Built an end-to-end lakehouse solution on Google Cloud to collect, process, and analyze
rental apartment market data. Developed a Python-based ingestion pipeline that
retrieves ~250 apartment listings daily via API, stores raw historical snapshots in
BigQuery, and automates workflows using Google Cloud Workflows. Implemented ELT
transformations with dbt following the Medallion Architecture (Bronze/Silver/Gold),
including data normalization, historical tracking, and incremental models for identifying
new and removed listings. Delivered business-ready datasets and interactive market
insights through a Looker Studio dashboard.
Tech Stack: Python, Google Cloud Storage, BigQuery, dbt, Google Cloud Workflows, SQL,
Parquet, Looker Studio, ELT, Medallion Architecture.
• HR Dashboard
Created an HR dashboard to analyze employee performance and attrition metrics. Data
was normalized, imported into MySQL, and then analyzed and visualized in Power BI,
providing actionable insights into HR trends.
• Laptop Prices Analysis Dashboard
Developed a Power BI dashboard to analyze laptop pricing trends based on
specifications. The dataset was normalized and imported into MySQL, allowing for
accurate and efficient analysis in Power BI.
• Solved 80+ data manipulation and SQL problems on LeetCode (focus on Pandas and
query optimization).

Additional Information

• Fluent in Ukrainian
• Proficient in English