About Graphisoft

Graphisoft® empowers teams to design great buildings through award-winning software solutions, learning programs, and professional services for the AEC industry. Our award-winning products and solutions support OPEN BIM for workflow transparency, longevity, and data accessibility for built assets.  Archicad®, the architects’ BIM software of choice, offers a complete end-to-end design and documentation workflow for architectural and integrated architectural and engineering practices of any size. BIMx®, the most popular mobile and web BIM app, extends the BIM experience to include all stakeholders in the building design, delivery, and operations lifecycle. BIMcloud®, the AEC industry’s first and most advanced cloud-based team collaboration solution, makes real-time collaboration possible across the globe regardless of the size of the project and the speed or quality of the team members’ network connection. DDScad solutions support users with intelligent Mechanical, Electrical, and Plumbing (MEP) design tools, integrated calculations, and comprehensive documentation of all building system disciplines. Graphisoft is part of the Nemetschek Group. To learn more, visit more visit www.graphisoft.com 

Role Overview

The Senior Data Analyst reports directly to the VP of Customer Success and operates as a key strategic partner to the Revenue Operations, Finance, and Product leadership teams. This role owns the end-to-end data strategy powering customer insights, retention analytics, and predictive modeling that inform executive decision-making. The position combines deep technical expertise in scalable data systems with business acumen to shape customer health strategies, efficiency metrics, and automation frameworks across the organization.This senior role governs data architecture, quality, and analytics initiatives that directly influence revenue growth, churn reduction, and operational excellence.

Responsibilities

• Define and execute the enterprise data strategy for Customer Success, ensuring consistent, harmonized customer data across global CRM, billing, product, and support ecosystems.
• Lead design and implementation of automated, high-reliability data pipelines and event-streaming architectures to serve analytics, machine learning, and executive reporting needs.
• Partner with executives across functions (RevOps, Finance, Product, Marketing) to translate strategic priorities into measurable data-driven programs.
• Oversee data governance, quality, and compliance standards across all Customer Success systems; establish organization-wide frameworks for validation, lineage tracking, and access control.
• Direct development of advanced predictive analytics solutions to quantify health scores, renewal risk, and adoption patterns, integrating AI/ML-driven forecasting models into business processes.
• Lead the integration between Customer Success and central Data & Architecture teams to align schema structures, metadata standards, and unified data contracts.
• Serve as strategic advisor to the VP Customer Success and the CFO for executive dashboards, KPI frameworks, and strategic investment modeling.
• Represent the Customer Success data function in global steering committees, ensuring data strategy supports sustainable growth, resource allocation, and transformation programs.

Qualifications

• 8+ years of experience in data engineering, analytics strategy, or business intelligence leadership roles in a global SaaS organization.
• Expertise in enterprise-scale data integration using modern stack technologies (SQL, Python, dbt, Fivetran, Airflow, Databricks, Snowflake, or equivalents).
• Proven experience designing and operationalizing cross-functional data strategies that improve business KPIs and executive decision quality.
• Strong understanding of Customer Success ecosystems (ChurnZero, Gainsight, Totango, or similar) and their integration with CRM, billing, and product analytics data.
• Exceptional communication and stakeholder management skills, with executive presence and ability to influence at C-level.
• Degree in Data Science, Engineering, or a business-related field (Master’s or MBA preferred).

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