Передусім, Київстар — це український телекомунікаційний оператор, послугами якого користується понад 26 млн абонентів. Київстар входить до складу міжнародної групи VEON Ltd, офіс якої знаходиться у Нідерландах. Акції Групи торгуються на фондових біржах NASDAQ, Нью-Йорк та Euronext, Амстердам.
16 сентября 2021

Azure Data Analyst (Cloud Big Data)

Киев, удаленно

Kyivstar is looking for Azure Data Analyst who will analyze complex, high-volume, high-dimensionality data from varying sources using a variety of tools and data analysis techniques.

The candidate should also be an effective communicator capable of independently driving issues to resolution and communicating insights to both technical and non-technical audiences.

We offer:

• A unique experience of working for the largest and most beloved mobile operator in Ukraine;

• Real opportunity to ship digital products to millions of customers;

• Remote work with possibility to visit the office;

• Onboarding program which can help with fast on-line adaptation;

• A competitive salary;

• Annual bonus;

• Paid sick leave and vacation;

• Financial aid in different life situations;

• Flexible working hours;

• Medical and life insurance;

• Great possibilities for professional development and career growth;

• Friendly & Collaborative Environment.


• 4+ years in Data Engineer, Data Analyst or another quant-focused field;

• Experience in database technology with solid understanding and hands-on skills with SQL (is a must);

• Ability to understand, translate and map business and product questions into analysis projects; 

• Ability to analyze large datasets;

• Experience building large scale data sets in Azure, AWS, Hadoop or similar big data environments; 

• Agile knowledge;

• Microsoft Azure Fundamentals certification is a plus.


• Preparing business requirements and technical specification by transformation Customer idea to real use cases;

• Develop analytical data sets in Azure or internal Big Data Environments which can be used for analytics and data science;  

• Supporting the data products in identifying and revising issues;

• Providing technical expertise on data storage structures, data mining, and data cleansing;

• Preparing Product documentation.