Data Engineering & Analytics for Demand Forecasting Internship

Job Description:

Job Description

► Support the development and maintenance of data pipelines for demand forecasting using Azure Data Factory (ADF), SQL, and Databricks
► Analyze and validate datasets (e.g., sales, point-of-sale, pricing, and inventory data) to ensure data quality, consistency, and usability
► Prepare, transform, and integrate data from different source systems, focusing on feature engineering to enhance the predictive power of forecasting models
► Assist in monitoring, troubleshooting, and optimizing data workflows and ETL/ELT processes in the cloud environment
► Support the evaluation of forecasting model results and performance, identifying areas for improvement and contributing to model refinement discussions
► Create and maintain insightful reports and dashboards (e.g., in Power BI) to support business monitoring, data validation, and model performance tracking
► Collaborate with business and technical teams to understand requirements and improve data availability for demand planning

Candidate Requirements:

Qualifications

► Engineering, Information Systems, or a related field with a focus on data analytics, programming, or cloud technologies
► English (written and spoken) is required
► First experience with data analysis and data processing (e.g., SQL, Python, Power BI)
► Basic understanding of databases, ETL/ELT processes, or data pipelines
► Interest in cloud-based data engineering, ideally with first exposure to Azure, Azure Data Factory, or Databricks.
► Experience with SQL and ideally some programming skills in Python
► Bonus: Knowledge of statistical concepts, machine learning fundamentals, data modeling, APIs, or version control (Git)
► Strong analytical and structured way of working
► Curious and eager to learn new technologies and business processes.
► Proactive mindset and hands-on attitude
► Comfortable working both independently and collaboratively in an international team