Masters 101 Internship Program: Data Analyst

**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**

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