Контактна інформація

Отримати контакти цього кандидата можна на сторінці https://www.work.ua/resumes/6446601/

Досвід роботи

Junior Data Analyst

з 04.2026 по нині (7 місяців)
Reading Analytics Portfolio Project, Львів (IT)

GitHub: https: https://github.com/Luhova-Viktoriia/Reading_Analysis

Designed and developed an end-to-end data analytics project based on a self-collected dataset of personal reading activity.
Built and maintained a normalized PostgreSQL database with relational schema design and data modeling.
Wrote SQL queries using joins, CTEs, window functions, aggregations and data validation techniques to analyze reading patterns.
Created interactive Power BI dashboards to visualize reading trends, genres, authors, formats and yearly insights.
Managed the complete analytics workflow, including data collection in Excel, cleaning, transformation, database implementation, visualization and GitHub documentation.

Освіта

Львівський національний аграрний університет

Будівництва та архітектури, архітектура та містобудування, Львів
Вища, з 2012 по 2018 (6 років)

Бакалавр архітектури (2016 р.) – Львівський національний аграрний університет.
Магістр архітектури (2018 р.) – Львівський національний аграрний університет.

Додаткова освіта та сертифікати

CANactions School - Advanced Architectural Program 'Integrated Spatial Planning for Amalgamated Hromadas'

2018-2019, 11 місяців

Знання і навички

• PostgreSQL
• DBeaver
• MS Power BI
• Tableau
• MS Excel

Знання мов

Англійська — вище середнього

Додаткова інформація

I am looking for a Junior Data Analyst position where I can apply my skills in SQL (BigQuery, PostgreSQL), Power BI, Tableau and Excel.

I cover the full cycle: collecting and auditing data, designing the database and the model, analysing it in SQL and building dashboards that answer one specific question.

Recent work:
a marketing mart joining four unrelated BigQuery tables (~12M rows) into a single campaign payback view;
a books analytics project — data collected and digitised in Excel, duplicates cleaned, a relational model designed and implemented in PostgreSQL, insights visualised in Power BI.

How I work: I check data before I trust it — empty columns, duplicates and mismatched keys are found by querying, not by assuming. I document the decisions behind a model so the numbers can be reproduced, stay patient with the slow half of the job, and deliver on the agreed date.

Background in architecture and urban planning (2018–2025), where analysis meant justifying decisions with evidence — now I do the same with data.