Data Engineer

As Hungary’s most attractive employer in 2025 (according to Randstad’s representative survey), Deutsche Telekom IT Solutions is a subsidiary of the Deutsche Telekom Group. The company provides a wide portfolio of IT and telecommunications services with more than 5300 employees. We have hundreds of large customers, corporations in Germany and in other European countries. DT-ITS recieved the Best in Educational Cooperation award from HIPA in 2019, acknowledged as the the Most Ethical Multinational Company in 2019. The company continuously develops its four sites in Budapest, Debrecen, Pécs and Szeged and is looking for skilled IT professionals to join its team.

Job Description

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.

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.
• Practical experience with containerization and Infrastructure as Code technologies such as Docker, Kubernetes, and Terraform to deploy, manage, and automate scalable infrastructure environments.
• Knowledge of security, compliance, and access management practices, including RBAC, IAM, encryption, anonymization, and adherence to regulations such as GDPR and CCPA.
• Strong collaboration and operational skills, including working closely with analysts, data scientists, and stakeholders, while managing multiple priorities and staying updated on emerging trends and best practices in data engineering.
• Excellent written and verbal communication competences in English language.
• Proficiency in Jira & Confluence.

Advantage:

• Experience working in SAFe environment.
• German language knowledge