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# Data Analyst

- **Company:** KWS Berlin GmbH
- **Location:** Berlin, Germany
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Data Analysis, Big Data, Data Governance, Database Queries, Python (Programming Language), Power BI, SAP (Applications), Microsoft Power Automate, SAP S/4HANA, SAP Ariba, Data Management, Data Pipelines, Powerapps
- **Published:** August 5, 2026
- **Apply:** https://www.jobs.de/job/data-analyst-focus-source-pay-mwd-mwd-1745254

## About the Role

* Bachelor's degree in Analytics, Economics, Engineering, Business Administration, or related field.
 * Proven experience in Procurement, Finance, Source-to-Pay (S2P), or Spend Analytics environments.
 * Experience with Master Data Management (MDM), data governance frameworks, and data quality monitoring.
 * Solid understanding of Source-to-Pay processes and familiarity with SAP S/4HANA.
 * Experience working with large datasets and translating business requirements into scalable analytics solutions.
 * Desirable experience in Power Apps, Power Automate and SAP Ariba.
 * Proficiency in BI tools (Power BI, SAP SAC, Datasphere) and process mining (Celonis).
 * Strong SQL skills; Python or R is a plus.
 * Strong analytical mindset, attention to detail, and proactive approach.
 * Fluent English; German is a plus.

## Description

KWS Berlin GmbH is looking for a Data Analyst with focus on Source-to-Pay (m/w/d) who is keen on translating business requirements into analytics solutions and operating and optimizing data pipelines with strong governance and Master Data standards. This position is unlimited and available on a full-time basis (38 hours/week) in Berlin.
Aufgaben

 * Translate business requirements into analytics solutions and collaborate across the full project lifecycle.
 * Operate and optimize data pipelines (ERP, S2P suite, AP, vendor master) with strong governance and master data management standards.
 * Perform diagnostic and predictive analyses to identify value levers (e.g., price/volume variance, payment term optimization).
 * Partner with cross-functional teams to define KPI standards, maintain data dictionaries, and ensure a single source of truth.
 * Support process mining and advanced analytics use cases (e.g., Celonis) to uncover inefficiencies.
 * Monitor and manage the Source-to-Pay (S2P) analytics landscape for stability, scalability, and compliance.
 * Drive adoption and change management for analytics solutions across S2P.
 * Build functional analytics capabilities within the S2P organization.


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