Principal SAP Finance & Data

Helsing's finance systems are scaling fast, and this role exists to ensure they scale with rigour. As Principal SAP Finance & Data, you will own SAP S/4HANA end-to-end: understanding its configuration, identifying where technical debt lives, and resolving it. Your immediate focus will be a thorough audit of the current SAP landscape, the elimination of manual workarounds, and a material acceleration of the month-end close cycle. Over time, you will set the standard for how Finance Transformation uses data and automation across Helsing, managing the Finance Data Engineer and translating technical complexity into plain financial language for all stakeholders. This role carries a clear trajectory toward SAP Solution Architect and Process Owner.

The day-to-day

• Own and execute the SAP S/4HANA improvement roadmap, including configuration, module ownership across FI, CO, TR and MM, release planning, and the elimination of accumulated technical debt.
• Configure, test, and approve SAP changes directly, ensuring hands-on accountability rather than vendor dependency for standard tasks, and partner with the Finance Data Engineer to design the data architecture connecting SAP to Abacum and Citi.
• Govern the Finance Data Lake including data modelling, lineage, access controls, and quality SLAs, and manage vendor relationships with SAP, Abacum, and Citi.
• Design self-healing finance pipelines with automated anomaly detection, root-cause classification, and auto-remediation, and apply process-mining tools such as Celonis to map SAP transaction flows and identify optimisation opportunities.
• Represent Finance Technology in external audits, and communicate technical constraints clearly to Finance Operations, Engineering, Treasury, HR, and Legal.

You should apply if you

• Have built and owned SAP S/4HANA in practice, with deep configuration knowledge of FI and CO and working familiarity with TR and MM, and can operate independently of a vendor team for standard tasks.
• Are fluent in SQL and data modelling, and comfortable writing and reviewing Python scripts for data transformation and pipeline validation.