Data Architect (f/m/d)
About the Role
Location Germany Bayern Erlangen
1. Country: Germany
2. State/Province/County: Berlin
3. City: Berlin
4. Country: Spain
5. State/Province/County: Madrid
6. City: Madrid
7. Country: Spain
8. State/Province/County: Catalonia
9. City: Barcelona
10. Country: Portugal
11. State/Province/County: Lisboa
12. City: Lisbon
13. Country: Portugal
14. State/Province/County: Porto
15. City: Porto
Remote vs. Office Hybrid (Remote/Office) Company Siemens Energy Global GmbH & Co. KG Organization EVP Global Functions Business Unit Digital Products and Solutions Full / Part time Full-time Experience Level Experienced Professional A Snapshot of Your Day As a Data Architect in the Scalable Core team, you will design the data architecture powering our AI, ML, and GenAI platforms. You’ll enable secure, efficient data flows across cloud, on-premises, and edge environments, and define models, governance, and standards in collaboration with engineering, MLOps, and platform teams. Your work will drive the performance, reliability, and trust of all our data-driven solutions.How You’ll Make an Impact
16. Design and evolve end-to-end data architectures for ingestion, processing, storage, and access across hybrid environments.
17. Define robust data models, APIs, and metadata strategies to support AI/ML, analytics, and backend service use cases.
18. Establish data quality, lineage, and compliance frameworks to ensure secure and trustworthy data use.
19. Collaborate across teams to align on data interfaces, formats, and flows that enable efficient model training and service integration.
20. Define and implement data governance policies, lifecycle management, and cataloging practices.
21. Evaluate and integrate modern data technologies (, streaming platforms, data lakes, cloud-native services) aligned with enterprise strategy.
What You Bring
22. Master’s degree in computer science, Data Engineering, Information Systems, or related field, or equivalent experience
23. Extensive experience designing scalable data architectures, modern data platforms, and robust ETL pipelines
24. Strong expertise in data modeling, architecture patterns, and cloud-native data technologies
25. Proficient with tools such as Apache Kafka, Spark, Snowflake, Delta Lake, or cloud equivalents (Azure/AWS/GCP)
26. Solid knowledge of data security, governance, compliance (, GDPR), and enterprise integration patterns
27. Strategic, collaborative approach with the ability to set standards and **design** technical roadmaps (bonus: experience supporting AI/ML, LLMs, or GenAI)