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# SAP Data Quality Business Analyst

- **Company:** SAP LTD.
- **Location:** United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Microsoft Excel, Profiling, Data Governance, Data Mining, Data Profiling, Power BI, SAP (Applications), SAP NetWeaver Data Management, Tableau (Software), Technical Data Management Systems, SAP S/4HANA, Data Management
- **Published:** October 1, 2026
- **Apply:** https://computerjobs.com/us/en/mob/job/1E11529FAAE8A30113

## About the Role

* 5+ years' Business Analysis experience, including hands-on experience within a manufacturing or similarly complex operational environment.
 * S/4HANA experience
 * Strong Data Quality and Master Data Management (MDM) experience, including requirements capture, data profiling, governance, KPIs, SLAs and data quality improvement.
 * Experience across key master data domains, including Material, Customer, Vendor and Finance, with understanding of BOMs and product/manufacturing data.
 * Strong SAP/ERP and PLM understanding,
 * Strong analytical and stakeholder skills, including data extraction/profiling, advanced skills in tools such as Excel, Power BI, Tableau etc. with the ability to translate complex data issues into clear business requirements.

## Description

SAP Data Quality Business Analyst - Oct Start - \u00a3Market Rate/day Inside IR35 paid to the umbrella - 9 months initially - Hybrid/UK, * Gather and translate complex business and manufacturing requirements into measurable data quality rules, standards and validation criteria.

 * Define and implement Data Quality KPIs and SLAs, covering accuracy, completeness, consistency, timeliness, validity, duplication and issue resolution.
 * Perform data profiling, mapping and root-cause analysis, identifying process/system issues and recommending controls to prevent poor-quality data at source.
 * Define requirements for automated data quality dashboards and reporting, working with analytics teams to provide operational and leadership-level visibility of data health.
 * Strengthen data governance and stewardship, establishing ownership, supporting Data Champions, improving processes and driving adoption of new data standards across cross-functional teams.


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