Data Quality and Control Analyst(m/w/x)

Requirements

• Bachelor’s/Master’s degree in Data/Computer Science, Engineering, Information Systems, Finance/Accounting or similar
• 4-8+ years experience in data quality, data governance, controls, reconciliation, finance reporting, or close-critical analytics environments
• Strong SQL skills (profiling, reconciliation logic, variance analysis)
• Ability to work confidently with large transactional and dimensional datasets
• Automation mindset
• Hands-on experience with Python or similar
• Experience with data testing frameworks
• Working knowledge of modern data platforms (lakehouse/warehouse concepts, orchestration, CI/CD/DataOps, monitoring/alerting)
• Understanding of production-grade concepts (SLOs, runbooks, incident response)
• Understanding of Finance processes and data flows (GL, revenue, billing, cost allocation)
• Exposure to SAP S/4 and/or Finance reporting stacks (BW, Group Reporting) (advantage)
• Familiarity with governance, security, access patterns for Finance-grade controls (RBAC, SoD, masking, audit logs)
• Strong documentation discipline
• Excellent analytical skills
• Excellent communication skills
• Excellent stakeholder-management skills
• Ability to explain issues, materiality, remediation options to Finance/engineering audiences
• Business-fluent English
• German language skills (advantage)

Tasks

• Define the Finance data quality framework
• Maintain the Finance data quality framework
• Design automated data quality tests
• Implement automated data quality tests
• Embed validation gates into DataOps CI/CD
• Build automated Finance reconciliations and tie-outs
• Operate automated Finance reconciliations and tie-outs
• Monitor and alert on Finance data products
• Monitor and alert on Finance reporting services
• Maintain runbooks and escalation paths
• Manage data exceptions end-to-end
• Reduce recurring data quality breaks
• Maintain audit evidence packages
• Support month-end and quarter-end close
• Produce close dashboards and exception packs
• Manage freeze windows for KPI versions
• Coordinate sign-off with Finance stakeholders
• Ensure data governance and auditability
• Support audit and control testing requests
• Collaborate with engineers and Finance SMEs
• Define data contracts (SLAs/SLOs)
• Improve upstream data quality
• Standardize KPI inputs and definitions
• Drive continuous improvement and standardization
• Create reusable control templates and patterns
• Document data quality best practices
• Coach team members on Finance controls
• Coach team members on quality-by-design

Work Experience

Education

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