Data Architect (REF5750O)
Employer · Deutsche Telekom IT Solutions
Database administrator
Systems analystSoftware developerFull-timeSzeged
We are looking for a talented and experienced Data Architect to join our team. The successful candidate will play a central role in shaping our data landscape across multiple value streams, requiring deep expertise in data integration, data modelling, and analytical engineering.
Tasks
- Design and maintain enterprise-wide data models, including conceptual, logical, and physical layers
- Lead data architecture for core platforms and support cross-value-stream data requirements
- Define data standards, naming conventions, and modelling best practices
- Evaluate and recommend appropriate data storage patterns (relational, dimensional, lakehouse, graph)
- Architect and oversee data pipelines and ETL/ELT processes across source systems
- Design integration patterns for batch, near-real-time, and streaming data flows
- Ensure robust data lineage, traceability, and auditability across all pipelines
- Collaborate with engineering teams to implement scalable, resilient integration solutions
- Develop semantic and analytical data models that serve BI, reporting, and advanced analytics use cases
- Partner with analytics and data science teams to define trusted data products
- Champion a self-service data culture by enabling reusable, well-documented data assets
- Define and enforce data quality rules, validation frameworks, and remediation processes
- Contribute to data governance policies, data cataloguing, and metadata management
- Work with stakeholders to manage data contracts and SLAs
- Act as a trusted data advisor across multiple value streams and business units
- Facilitate technical workshops and design reviews with engineering and product stakeholders
- Communicate complex data architecture decisions clearly to both technical and non-technical audiences
Requirements
- 5 years of experience in data architecture, data engineering, or a closely related role
- Strong proficiency in data modelling techniques: relational, dimensional (Kimball/Inmon), and Data Vault
- Hands-on experience with data integration tools and frameworks (e.g. Apache Kafka, dbt, Spark, Talend, or similar)
- Solid understanding of cloud data platforms (AWS, GCP, or Azure) and modern data stack components
- Advanced SQL skills and familiarity with Python or Scala for data engineering tasks
- Proven ability to translate business requirements into scalable data architecture solutions