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Big Data Analyst

Pubblicato il 25-08-2026 - Kyivstar in Italia

We are looking for a Data Analyst to work with large-scale datasets in a cloud environment using SQL (Trino) and PySpark. The role focuses on building datasets, identifying application hosts, and creating audience segments based on user behavior.
Responsibilities
Querying and processing large datasets using Trino (SQL).
Working with data in AWS environment using PySpark.
Identifying and analyzing application hosts / domains based on traffic data.
Building audience segments based on website activity, call data, behavioral patterns and segment rules.
Monitoring and auditing accuracy and completeness of collected data.
Organizing data into usable formats.
Creating basic visualizations and reports (Power BI or similar).
Generating information and insights from data and identifying trends and patterns.
Conducting A/B tests to understand and evaluate quality of data models.
Developing and maintaining automated data processes.
Requirements
Strong experience with SQL (Trino, Presto, or similar).
Experience working with large-scale datasets in distributed environments (AWS, PySpark).




Excellent knowledge and confident Excel user.
High attention to details.
Gaining knowledge from a large amount of data.
Basic knowledge of statistics.
Experience with Power BI or other BI tools.
Strong analytical thinking and problem-solving skills.
Familiarity with Jira, Confluence.
Will be a plus
Experience with telecom data.
Understanding of web/app traffic and domain classification.
Knowledge of Python.
We offer
Work in one of the largest and most beloved telecom company in Ukraine.
Opportunity to work with large-scale real-world data.
Remote work with possibility to visit the office.
Flexible working hours.
Onboarding program which can help with fast on-line adaptation.
Competitive salary and annual premio.
Paid vacation and sick leave.
Medical and life insurance.
Financial aid in different life situations.
Great possibilities for professional development and career growth.
Friendly and coll

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