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Data architect (f/m/d)

Erlangen
Siemens Energy
Inserat online seit: 14 April
Beschreibung

Data Architect (f/m/d)

About the Role

Location Germany Bayern Erlangen
1. Country: PORTUGAL
2. State/Province/County: Lisboa
3. City: Lisbon

4. Country: GERMANY
5. State/Province/County: Berlin
6. City: Berlin

Remote vs. Office Hybrid (Remote/Office) Company Siemens Energy Global GmbH & Co. KG Organization EVP Global Functions Business Unit Strategic Procurement Full / Part time Full-time Experience Level Mid-level Professional

AA Snapshot of Your Day

We are looking for a Data Architect (f/m/d) to define and govern the architecture of our modern data platform. The role focuses on establishing technical standards, data governance, and architectural guidelines, while working closely with external consulting partners and internal engineering teams to ensure high-quality implementation.A key objective of the role is ensuring that enterprise data is structured and governed to support advanced AI use cases, particularly Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) applications.How You’ll Make an Impact
7. Define and maintain the architecture and standards for the enterprise data platform
8. Establish and enforce data governance, development guidelines, and quality standards
9. Provide architectural oversight for data pipelines, models, and integrations delivered by external consultants
10. Review and validate implementations to ensure alignment with architectural principles and best practices
11. Support the creation of reliable data foundations for GenAI, Agentic AI, and RAG use cases
12. Promote modern engineering practices, including version control and CI/CD
What You Bring
13. Experience in data architecture or senior data engineering within modern cloud data platforms
14. Strong expertise in SQL, Snowflake, and data modeling frameworks (, dbt)
15. Solid Python skills for data processing, automation, or platform tooling
16. Experience with API integrations, data streaming architectures, and cloud platforms (preferably AWS)
17. Understanding of SAP data structures in Supply Chain Management divison, SAP MM (SAP FI knowledge is an advantage)
18. Experience establishing data governance frameworks and guiding external delivery teams

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