- Young & supportive team - in a fast-growing international business environment
- Learn & develop yourself - help you craft your career path with (INNIO learning, free language courses according to business needs
- Hybrid working - 50% Office, 50 % Home Office with flexible working hours
- Cafeteria package with various options - SZÉP Card, Cash option, Nursery & kindergarten support
- Medicover Spring White Package- from the first day of employment
- Easily accessible location - in the heart of the most vibrant campus area in Budapest (location: 13rd District, easy to approach by Metro Line 3)
- Take a break - Recharge your batteries with free coffee and tea selection in the kitchen area
- Live an active lifestyle – activate your AYCM pass
The Data Engineer Expert works together with Data Analysts, BI Developers and Requirements Engineers to create the foundation for all analytical projects. This includes building and maintaining data pipelines that extract, transform, and load (ETL) data from various sources into a central repository and from here to the corresponding project.
- Design and implement scalable and robust data pipelines to support analytics and data processing needs
- Develop and maintain database architectures, including data lakes and data warehouses
- Ensure data quality and consistency through data cleaning, transformation, and validation processes
- Collaborate with Data Analysts, BI Developers and Requirements Engineers to gather requirements and deliver data solutions that support business objectives
- Optimize data retrieval, develop pipelines and physical data models for reports and various analytical project needs
- Implement data security and privacy policies to comply with legal and regulatory requirements
- Document the created pipelines
- Completed university studies with a focus on Business & administration, data science, computer science, information management, statistics, mathematics, or equivalent
- Fluency in English
- Professional experience in data analytics, business intelligence, financial or operational reporting
- Strong knowledge of and at least 6+ years of experience in pipeline creation with large data sets using SQL, NoSQL or Python
- Experience with cloud platforms (especially Azure, Databricks)
- Expertise in ETL tools (e.g., Apache Spark, Apache Flink)
- Understanding of data warehousing principles and technologies
