Senior Manager GTM Data Analytics & Engineering

Overview

In this role you will own and evolve TeamViewer’s GTM data architecture and analytics layer, enabling scalable revenue insights across Marketing, Sales, Customer Experience, and Finance. You’ll design durable data models, end-to-end ELT/ETL pipelines, and a semantic layer for self-service analytics, partnering with cross-functional teams. You’ll lead a small team of analytics engineers, balancing hands-on delivery with coaching to raise data quality and governance. This role sits at the intersection of Data Engineering, Analytics, and RevOps, with a focus on durable systems over ad-hoc reporting.

Responsibilities

• Design and own end-to-end GTM data architecture from source to BI consumption
• Build scalable data models for full-funnel and revenue analytics
• Develop and manage ELT/ETL pipelines integrating CRM, Marketing Automation, Finance, and Customer platforms
• Ensure reliable, monitored, well-documented data pipelines
• Collaborate with central data/engineering teams to align with architecture standards
• Own canonical data models for Marketing, Sales, Pipeline, Revenue, Retention, and Expansion
• Translate business processes into durable analytical schemas
• Standardize event, object, and metric definitions across systems
• Support complex revenue use cases like attribution, forecasting, cohort analysis, funnel metrics
• Ensure data models support historical accuracy and forward-looking analysis
• Define exposure of transformed data to BI tools (Power BI, Tableau)
• Build and maintain a governed semantic layer for self-service analytics
• Reduce duplication and ad-hoc reporting debt
• Ensure reconciliation between ERP & CRM data in BI
• Establish data quality checks, validation rules, and reconciliation processes
• Own metric governance in partnership with RevOps and Finance
• Document, version, and control core datasets
• Act as accountability for GTM data correctness and consistency
• Eliminate manual reporting through engineering solutions
• Enable forecasting models, anomaly detection, and AI-driven insights
• Lead and develop a small analytics engineering team
• Set engineering standards for data modeling, pipeline development, testing, and documentation
• Collaborate with RevOps, Finance, IT, and central Data teams
• Translate analytical needs into architecture decisions for GTM and Finance
• Support executive reporting by ensuring a sound data foundation

Requirements

• 7–10+ years in data engineering, analytics engineering, or advanced BI
• Experience designing and maintaining analytical data architectures including data warehousing
• SQL-based transformation layers and data models at scale
• Experience integrating multiple SaaS systems into a unified analytics environment
• Experience with GTM, revenue, or commercial data in a SaaS business
• Experience leading and coaching technical analytics or data teams

Additional Information

• onsite onboarding in HQ
• compensation and equity including bonuses
• pension plan premium funded
• hybrid and flexible work time
• work from abroad program up to 40 days
• local gym discounts / corporate benefits platform