Data Engineer (REF5482T)

Department and Project

This position is within the Tolling Services team of Deutsche Telekom IT Solutions Hungary. The team consists of IT professionals specializing in electronic road-charging solutions. Together with our partners, we develop and operate intelligent, kilometer-based tolling systems for international customers, covering the entire business process (vehicle registrations, country booking, providing On-Board Units, position data transmission, charge calculation, and fleet billing). Leveraging digital intelligence and advanced technology, our tolling solutions facilitate seamless mobility across Europe. The team aims to enhance existing services and expand into new domains. As part of an international team collaborating with T-Systems International, you will play a key role in supporting our customers with cutting-edge tolling solutions.

Main tasks

As a Data Engineer:

• Data Pipeline Development
• Data Integration
• Data Warehousing
• Data Modelling
• Data Quality and Governance
• Performance Optimization
• Collaboration with Data Scientists/Analysts
• Technology Selection
• Security and Compliance
• Monitoring and Troubleshooting

Background and required skills:

• Bachelor or Master’s degree in the following areas: Computer science, Engineering, Information Technology, natural science, mathematics, business or equivalent work experience in IT
• Strong expertise in modern data engineering tools and technologies, including DeltaLake, SQL, Python, Tableau, QuickSight, Kafka, Apache Flink, Apache Doris, Superset, and Schema Registry for data processing, analytics, and visualization.
• Experience designing and building scalable ETL/ELT data pipelines that extract, transform, and load data from multiple systems into centralized data warehouses or data lakes while ensuring reliability and performance.
• Hands-on knowledge of integrating data from diverse sources such as databases, APIs, streaming platforms, and NoSQL systems using tools like MongoDB Atlas, Debezium, and Kafka Connect for CDC and real-time data streaming.
• Ability to automate and optimize data workflows, monitor pipeline health, and troubleshoot infrastructure or processing issues to ensure continuous, efficient, and high-performing data operations.
• Strong data modeling and data architecture skills, including designing schemas, maintaining data consistency, and implementing scalable storage solutions for large-scale analytics environments.
• Expertise in data quality management, including validation, cleansing, harmonization, and governance practices to ensure accurate, compliant, and trustworthy datasets across systems.
• Solid understanding of cloud and infrastructure engineering, especially AWS-based compute and storage environments, with experience optimizing scalability, reliability, security, and cost efficiency.