Senior Data Analyst, Veeam

• 5+ years of experience in a data analyst, business intelligence, or analytics engineering role, ideally within a SaaS or subscription-revenue environment
• Advanced SQL skills. You write efficient, well-structured queries and are comfortable working with large, complex datasets. Experience with modern cloud data platforms (e.g., Databricks, Snowflake, Redshift) is a strong plus
• Tableau expertise. You've built polished, production-grade dashboards from scratch — not just modified existing views. You understand calculated fields, LOD expressions, performance optimization, and publishing/governance workflows
• Executive communication skills. You're comfortable presenting to senior leaders, fielding tough questions, and distilling complex data into clear narratives
• Strong business acumen. You understand corporate performance metrics and SaaS fundamentals — ARR, MRR, NRR, churn, expansion, contraction — and how they connect to the broader business
• Self-directed and proactive. You take ownership of your domain, anticipate stakeholder needs, and don't wait to be told what to analyze. Strong critical thinking and intellectual curiosity are key
• If you thrive at the intersection of data, design, and business strategy, this role is for you

Desirable

• We're looking for a Senior Data Analyst to own the delivery of corporate dashboards and analytical insights that drive strategic decision-making across Veeam
• In this role, you'll be responsible for a broad portfolio of corporate metrics — with ARR and subscription revenue analytics as a primary focus — building, maintaining, and evolving the dashboards and reporting that senior leadership relies on to understand business performance
• Reporting to the Director of Data Analytics, this is a high-visibility position
• You'll work directly with VPs and C-level stakeholders to translate complex SaaS metrics into clear, actionable stories
• Own the Corporate Dashboard Portfolio: Design, build, and maintain Tableau dashboards spanning key corporate metrics, with a primary focus on ARR, incremental ARR, net revenue retention (NRR), acquisition, upsell, downsell, and churn
• Deliver Analytical Insights: Go beyond reporting — proactively surface trends, anomalies, and opportunities across corporate and revenue data and present findings to senior leadership
• Partner with Stakeholders: Serve as the primary analytics point of contact for executive and cross-functional teams, translating business questions into data-driven answers
• Write and Optimize SQL: Query large-scale databases to extract, transform, and validate data for dashboards and ad hoc analyses
• Maintain Data Quality: Collaborate with data engineering to ensure upstream data pipelines produce accurate, timely inputs for reporting
• Drive Continuous Improvement: Identify opportunities to improve existing dashboards, automate manual reporting, and introduce new analytical capabilities — including AI-assisted tools where appropriate
• Document and Standardize: Establish clear definitions, data dictionaries, and best practices for corporate and ARR-related metrics across the organization