Data Engineer (f/m/d)

Bachelor’s degree or higher in Data Science, Data Engineering, Business Intelligence, Business Administration, or related field. 2+ years of working experience as a Data Engineer or Data Warehouse Developer using Python or similar technologies. Hands-on experience with Microsoft Azure and AWS data engineering pipelines. Excellent knowledge of database and dimensional modeling techniques. Strong experience with Azure Data Factory, Azure Databricks, Python (NumPy, Pandas), ADLS, Azure Event Hub, and Azure SQL DB. Familiarity with AWS Glue, S3, Athena, Redshift, and Lambda is highly desirable. Excellent command of SQL, T-SQL, Python, and PySpark. Practical experience with Agile and Scrum methodologies. Strong communication and analytical skills. Ideally, experience working in a big data environment and exposure to AI/ML frameworks/libraries (MLlib, MLOps, Scikit-learn, TensorFlow, Matplotlib), Spark, and JSON.

Write clean and maintainable code following data warehousing best practices. Troubleshoot data transformation errors. Present findings and proposed improvements to stakeholders. Design and implement new Azure and AWS data pipelines and Databricks notebooks. Add new data points to existing Azure Analysis Services (AAS) cubes. Continuously identify and implement performance improvements. Ensure the quality, accuracy, and reliability of all data and reports.