Senior SAP Data Engineer

Senior SAP Data Engineer (Datasphere, BDC, SAC & Cloud Data Platform)

 

About the Role

We are looking for a Senior SAP Data Engineer to take a key role in building and scaling our cloud-native data platform with SAP at its core.

You will work across SAP data integration, semantic modeling, and analytics while contributing to a broader modern data ecosystem leveraging SAP Datasphere, SAP Business Data Cloud, and SAP Analytics Cloud, alongside Databricks, Microsoft Fabric, and Power BI.

This role sits at the intersection of SAP and modern data platforms, helping transform SAP data into trusted, business-ready data products that power reporting, planning, and advanced analytics across the enterprise.

• Location: Lisbon, Portugal
• Working hours: Full-time
• Contract type: Direct employmen - 1 year contract

 

What You’ll Do

• Design and implement data models and data products in SAP Datasphere
• Build and optimize cloud-native data pipelines from SAP S/4HANA and other SAP/non-SAP sources
• Integrate SAP data into the broader cloud data platform (Databricks, Microsoft Fabric)
• Work with SAP-native integration capabilities within SAP Business Data Cloud
• Develop analytical datasets consumed by SAP Analytics Cloud (SAC) and Power BI
• Implement delta handling, data harmonization, and scalable semantic layers
• Ensure high data quality, consistency, and governance across SAP and enterprise data assets
• Collaborate with business stakeholders (finance, supply chain, sales) to translate requirements into scalable data solutions
• Contribute to evolving our modern, cloud-native data architecture and platform standards

 

What We’re Looking For

• 5+ years of experience in data engineering, analytics engineering, or SAP data modeling
• Strong hands-on experience with SAP Datasphere
• Experience integrating data from SAP S/4HANA or SAP ECC
• Solid understanding of SAP data models (FI/CO, SD, MM, etc.)
• Experience with semantic modeling and data product design
• Strong SQL skills and understanding of data transformation logic
• Experience working in modern cloud data ecosystems (e.g., Databricks, Microsoft Fabric, Azure)
• Familiarity with Power BI or other BI tools

 

Nice to Have

• Experience with SAP Business Data Cloud (or similar SAP cloud integration frameworks)
• Hands-on experience with Databricks (Spark, Delta Lake) or Microsoft Fabric
• Experience with end-to-end data pipelines beyond SAP (ELT/ETL frameworks)
• Familiarity with Lakehouse architectures and medallion design patterns
• Experience with data governance and master data (e.g., SAP MDG/MDQ)
• Knowledge of planning processes (finance or supply chain)

 

Why Join Us?

We are building a modern, cloud-native data platform that combines SAP technologies (Datasphere, Business Data Cloud, SAC) with a broader ecosystem including Databricks, Microsoft Fabric, and Power BI.

Our goal is to move beyond traditional SAP reporting into a scalable, product-driven data platform, where SAP data is seamlessly integrated with enterprise data to power advanced analytics, AI, and decision-making.

You’ll be part of a team redefining how data is used—bridging SAP and the modern data stack to create real business impact.

 

How to Apply:

If you are ready to be a part of our exciting journey at STG, please, apply by including your resume and highlighting your experience, as well as any other relevant information you would like to share with us.

Thank you for considering this exciting opportunity.

 

Scandinavian Tobacco Group Talent Team

Scandinavian Tobacco Group is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

 

"Please be informed that this Direct Search is conducted exclusively by Scandinavian Tobacco Group. We do not accept applications from agencies, and we will not provide compensation for unsolicited CVs.