Experienced Data Engineer (f/m/d)
About the Role
Location Germany Bayern Erlangen
1. Country: GERMANY
2. State/Province/County: Berlin
3. City: Berlin
4. Country: ROMANIA
5. State/Province/County: Bucuresti
6. City: Bucharest
7. Country: UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
8. Country: PORTUGAL
9. State/Province/County: Lisboa
10. City: Lisbon
Remote vs. Office Hybrid (Remote/Office) Company Siemens Energy Global GmbH & Co. KG Organization SE CFO Business Unit Accounting Full / Part time Either Experience Level Experienced Professional A Snapshot of Your Day As an Experienced Finance Data Engineer, you build and maintain the data pipelines and infrastructure that power Siemens Energy’s digital finance solutions. You work closely with finance data architects, data stewards, and BI/analytics teams to ensure high quality, governed, and AI-ready data is available for reporting, analytics, and AI solutions. Your work is foundational for data driven decision making across Finance.How You’ll Make an Impact
11. Build scalable data pipelines for ingestion, transformation, and delivery of finance relevant data
12. Integrate and harmonize data from ERP, external sources, and business domains into a Cloud Data Platform for Finance
13. Implement validation, monitoring, and lineage in line with Siemens Energy’s governance and quality standards
14. Automate data workflows and integrations to improve efficiency, reliability, and repeatability
15. Collaborate with product owners, architects, platform engineers, AI experts and finance stakeholders to deliver business driven data solutions
16. Evaluate and apply modern data engineering tools ( dbt, AWS, Snowflake) to enhance scalability and innovation
What You Bring
17. University degree in Computer Science, Data Science, Engineering, Finance, or a related field
18. Hands on data engineering experience in enterprise environments, ideally within the finance domain
19. Proven experience building data pipelines on modern platforms ( Snowflake, Azure, or AWS)
20. Strong SQL skills and good knowledge of Python or similar scripting languages
21. Familiarity with data governance and AI-readiness and how to reflect them in pipeline design
22. Ability to work in Agile, cross functional teams and communicate effectively with both technical and business stakeholders