Data Quality and Control Analyst 80-100%

Join us in the top league! At Sunrise, we think bigger, go further and create new ideas. For us working culture means achieving great things together. It's where respect and innovative ideas combine with real teamwork - every voice counts, every perspective makes us stronger. Our passion spurs us on to try new things and grow continuously. Sounds like you? Then join our success story.

At ADAO (AI, Data and Agentic Enablement Office) we bring people together to unlock the future of Sunrise through data, analytics, AI and agentic technologies. We think big, move with purpose, and turn ideas into real impact for our customers and teams. ADAO is where innovation meets trust: we build strong data foundations, scale safe and reliable AI capabilities, and empower business units through our Hub and Spoke model to deliver meaningful results across the company.

In this role you will be the Finance Pod's point of expertise for data quality, reconciliation and control discipline across the Finance Single Source of Truth (SSOT), certified Finance data products, the enterprise semantic layer and close-critical reporting outputs. Reporting to the Head of Data & Reporting Platforms engineering (your chapter/functional home) and allocated to the Finance Pod, you will design, implement and operate automated quality checks, alerts and tie-outs that enable Finance-grade reliability, auditability and sign-off readiness.
You will partner closely with Finance stakeholders (Controlling/FP&A, Finance Operations, Internal Control) and ADAO engineers to prevent quality issues upstream, manage exceptions efficiently, and maintain evidence packages that withstand audit scrutiny while reducing manual close effort. The role contributes to scaling reusable patterns for quality-by-design, reconciliations, and governance controls across Pods.

YOUR CHALLENGE:

• Define and maintain the Finance data quality & controls framework: control catalogue, ownership, cadences, materiality thresholds and acceptance criteria (completeness, accuracy, consistency, timeliness)
• Design and implement automated data quality tests across ingestion, transformation, curation and semantic KPI layers (SQL/Python), and embed validation gates into DataOps CI/CD (testing, deployment, rollback readiness)
• Build and operate automated reconciliations and tie-outs between key Finance sources and SSOT datasets (e.g., billing/revenue/GL flows; SAP Finance and reporting systems), including variance logic, drill-down explainability and evidence capture
• Run monitoring and alerting for Finance-critical data products and reporting services: freshness, pipeline failures, schema drift, threshold breaches and reconciliation gaps; maintain runbooks and escalation paths
• Operate exception management end-to-end: triage, root-cause classification, ownership routing, remediation tracking, and closure validation; reduce recurring breaks through structured problem management
• Support month-end/quarter-end close readiness: produce close dashboards and exception packs, manage freeze windows for KPI/semantic versions, and coordinate sign-off readiness with Finance stakeholders
• Ensure governance and auditability: lineage completeness, metadata quality, versioning/change approvals, retention of evidence, and traceability from source-to-reporting; support audit/control testing requests when needed 
• Collaborate with Data & Reporting Platforms engineers, analytics engineers and Finance SMEs to define data contracts (SLAs/SLOs), improve upstream data quality, and standardize KPI inputs and definitions to enable reuse
• Drive continuous improvement and standardization: create reusable control templates/patterns, document best practices, and coach Pod members on Finance-grade controls and quality-by-design
   

YOUR SKILLS:

• Bachelor's/Master's degree in Data/Computer Science, Engineering, Information Systems, Finance/Accounting or similar
• 4-8+ years of experience in data quality, data governance, controls, reconciliation, finance reporting, or close-critical analytics environments
• Strong SQL skills (profiling, reconciliation logic, variance analysis) and ability to work confidently with large transactional and dimensional datasets
• Automation mindset with hands-on experience using Python (or similar) and/or data testing frameworks to implement repeatable controls and evidence capture
• Working knowledge of modern data platforms (lakehouse/warehouse concepts, orchestration, CI/CD/DataOps, monitoring/alerting) and what "production-grade" means (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, etc.) is a strong advantage
• Familiarity with governance, security and access patterns relevant to Finance-grade controls (RBAC, SoD, masking, audit logs) and strong documentation discipline
• Excellent analytical, communication and stakeholder-management skills: able to explain issues, materiality and remediation options to both Finance and engineering audiences
• Business-fluent English required; German is an advantage

At Sunrise, you'll be working in a dynamic and multinational environment where every voice is heard, perspectives are shared and values are lived. Diversity isn't just a program for us, it's part of our DNA. By celebrating our differences, we achieve great things together.

Sunrise has partnered with «Advance - Gender Equality in Business». We've also been awarded the Swiss LGBTI label and «Fair-ON-Pay Advanced» certification as recognition for offering all our employees equal pay for work of equal value.

Ready to rise to the challenge? Then join the team and actively shape our future!

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