Data Analyst

Детали за позицијата

About The Position

We’re always on the lookout for ambitious, talented individuals who are eager to grow their careers and gain experience on exciting international projects. Right now, we’re looking for a Data Analyst Intern to join our Business Intelligence team. In this role, you’ll work with SQL and Power BI to support data-driven insights and contribute to impactful client projects. At our company, you’ll collaborate on global assignments, thrive in a supportive and friendly environment, and be part of a dream team that values curiosity, growth, and a true culture of knowledge-sharing.

What We Offer

Financial compensation
Mentorship and training opportunities
Valuable practical experience with work activities
Network with professionals in the field
Attending networking and social events
A dream team with a knowledge-sharing culture
A friendly working environment

Your Skills

Currently enrolled in the last year of studies or with a Bachelor’s Degree in computer science, computer engineering, or other equivalent fields
Experience with data querying or modeling with SQL (preferably Microsoft data stack).
Experience with building and maintaining basic data artifacts (e.g. ETL, data models, queries).
Basic experience with one or more industry analytics visualization tools (e.g. Excel, PowerBI, Tableau, Looker).
Knowledge of data modeling and data pipeline design.
Experience with relational and star schema data modeling concepts.
General curiosity and ability to reverse engineer an existing process/pipeline.
Ideas on how to improve code quality and optimizes BI processes (e.g., speed, cost, reliability).
Excellent knowledge of the English language is a MUST.
Excellent verbal/written communication skills and data presentation skills.
Strong analytical skills.
Self-starter or the ability to proactively find work or learning opportunities.

Your Responsibilities

The application of BI and DWH concepts to the support of specific business functions or processes (Examples: data ingestion, data validation, data cleaning, data processing, and ETL).
Use various tools (query interfaces) and concepts regarding data and databases (Examples: data flow diagrams, relational data modeling, user story, data dictionary, data lineage, source-to-target mapping).
Collecting and interpreting data.
Analyzing results and identifying patterns and trends in data sets.
Use one or more industry analytics visualization tools (e.g. Excel, PowerBI) and, as needed, statistical methods to deliver actionable insights to stakeholders.
Defining new data collection and analysis processes.
Troubleshoot data, analyses, and codes, research root causes, propose solutions and take ownership of the next steps for their resolutions.