Why This Role Stands Out
This hybrid role offers a unique opportunity to significantly impact a major SAP finance transformation and AI initiative by investigating and ensuring the integrity of financial data. You'll thrive here if you are a detail-oriented problem-solver with experience in SAP financial data and data quality, eager to trace data lifecycles and collaborate with diverse teams. Don't miss out on this chance to deepen your expertise and contribute to cutting-edge data initiatives.
Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
22 hours ago
Financial ReportingReconciliationSAP
Job Description
Data Quality Analyst
Length: 6 months
Hours: 40 per week
Location: Remote (CST or EST is preferred, but as long as they can work EST, anywhere is fine)
About the Role
We’re looking for a detail-oriented and naturally curious Data Quality Analyst - SAP who will act as a Data Quality Investigator/Lineage Analyst to support a broader SAP finance transformation and AI-enabled data platform initiative. This role will dig deeply into financial data to understand its quality, lifecycle, and movement across source systems, SAP, reporting tools, and the new platform.
The Data Quality Analyst - SAP will trace how data is created, transformed, adjusted, and consumed, investigating where errors or inconsistencies may be introduced along the way. This includes identifying the root causes of data-quality issues, mapping end-to-end data lineage, monitoring for possible data corruption, and examining manual activity such as top-side adjustments.
Rather than simply flagging symptoms in downstream reports, this person will work with finance, accounting, data, and source-system owners to determine where an issue originated and help ensure it is corrected at the source. This is an ideal opportunity for someone who enjoys getting into the weeds, following data across complex systems, and solving problems that affect the accuracy and reliability of financial reporting, analytics, automation, and AI-generated insights.
We’re looking for a detail-oriented and naturally curious Data Quality Analyst - SAP who will act as a Data Quality Investigator/Lineage Analyst to support a broader SAP finance transformation and AI-enabled data platform initiative. This role will dig deeply into financial data to understand its quality, lifecycle, and movement across source systems, SAP, reporting tools, and the new platform.
The Data Quality Analyst - SAP will trace how data is created, transformed, adjusted, and consumed, investigating where errors or inconsistencies may be introduced along the way. This includes identifying the root causes of data-quality issues, mapping end-to-end data lineage, monitoring for possible data corruption, and examining manual activity such as top-side adjustments.
Rather than simply flagging symptoms in downstream reports, this person will work with finance, accounting, data, and source-system owners to determine where an issue originated and help ensure it is corrected at the source. This is an ideal opportunity for someone who enjoys getting into the weeds, following data across complex systems, and solving problems that affect the accuracy and reliability of financial reporting, analytics, automation, and AI-generated insights.
What We're Looking For:
- Bachelor’s degree in Finance, Accounting, Information Systems, Data Analytics, Computer Science, or a related field
- Experience with SAP financial data, SAP tables, SAP reporting structures, or SAP-to-downstream data integrations
- Experience in data quality, data lineage, data analysis, financial systems analysis, data governance, or a similar investigative role
- Demonstrated ability to conduct root-cause analysis and trace data issues across multiple systems and transformation layers
- Experience mapping and documenting data lineage from source systems through integrations, data platforms, and reporting outputs
- Strong understanding of data lifecycles, including data creation, extraction, transformation, loading, adjustment, reconciliation, and reporting
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