Responsibilities
Data Architecture & Analytics Engineering
Design and own the end‑to‑end GTM data architecture, from source systems through transformation layers to BI consumption
Build and maintain scalable data models that support full‑funnel and revenue analytics
Develop and manage ELT/ETL pipelines integrating CRM, Marketing Automation, Finance, and Customer platforms
Ensure data pipelines are reliable, monitored, performant, and well‑documented
Partner with central data and engineering teams where applicable to align with broader architecture standards
Revenue & GTM Data Modeling
Own the canonical data models for Marketing, Sales, Pipeline, Revenue, Retention, and Expansion
Translate business processes into durable analytical schemas rather than report‑specific logic
Standardize event, object, and metric definitions across systems
Support complex revenue use cases such as lead attribution, forecasting, cohort analysis, funnel conversion, and lifecycle reporting
Ensure data models support both historical accuracy and forward‑looking analysis
BI Enablement & Semantic Layer
Define how transformed data is exposed to BI tools such as Power BI and Tableau
Build and maintain a governed semantic layer to enable self‑service analytics
Ensure dashboards are powered by consistent, reusable data models rather than embedded logic
Reduce duplication, manual calculations, and ad‑hoc reporting debt across the organization
Ensure seamless reconciliation capability between ERP & CRM data, managed through BI
Data Quality, Governance & Reliability
Establish data quality checks, validation rules, and reconciliation processes
Own metric governance in partnership with RevOps and Finance
Implement documentation, change control, and versioning for core datasets
Act as a point of accountability for GTM data correctness and consistency
Automation & Advanced Analytics Enablement
Eliminate manual reporting and spreadsheet‑based workflows through engineering solutions
Enable downstream use cases such as forecasting models, anomaly detection, and AI‑driven insights
Ensure data structures are suitable for experimentation and advanced analytics
Team Leadership
Lead and develop a small team of analytics engineers and senior analysts
Set engineering standards for data modeling, pipeline development, testing, and documentation
Balance hands‑on delivery with team growth and backlog prioritization
Build strong collaboration with RevOps, Finance, IT, and central Data teams
Stakeholder Partnership
Work closely with GTM and Finance leaders to translate analytical needs into data architecture decisions
Provide technical guidance on what is feasible, scalable, and sustainable
Support executive reporting by ensuring the underlying data foundation is sound
Experience
7–10+ years experience in data engineering, analytics engineering, or advanced BI roles
Proven experience designing and maintaining analytical data architectures, including data cube/data warehousing setup
Experience owning SQL‑based transformation layers and data models at scale
Experience integrating multiple SaaS systems & tools into a unified analytical environment
Experience working with GTM, revenue, or commercial data in a SaaS business with appropriate commercial acumen, capable of understanding the key drivers & priorities of different GTM teams including Marketing, Sales, Customer Success, Renewals, etc.
Experience leading & coaching technical analytics or data teams for both career development and big‑picture understanding
Required Skills
Advanced SQL and data modeling expertise
Strong understanding of ELT/ETL concepts and pipeline reliability
Experience working with modern analytics stacks and cloud data platforms
Strong understanding of revenue and GTM data structures
Ability to balance business requirements with long‑term architectural integrity
Clear, pragmatic communication with technical and non‑technical stakeholders
Preferred Qualifications
Background in Analytics Engineering (dbt‑style modeling approaches)
Experience supporting revenue forecasting or financial reporting models
Experience operating in multi‑region SaaS environments
Exposure to AI‑enabled analytics or ML‑ready data architectures
What we offer
Onsite Onboarding in our HQ office for an optimal start
Great compensation and benefits packages including company achievement bonus or sales bonus, company stocks and regular salary reviews
Premiums for the private pension plan (BAV) up to the maximum amount are topped up by TeamViewer
Public transport friendly offices
Option to lease an e‑bike (Germany only)
Special terms for local gyms
Access to Corporate Benefits platform with many discounts
Regular Team events and company‑wide celebrations
Open door policy, no dress code rules, frequent all Hands and Leadership Lunches
Hybrid and Flexible work time with up to 50% home office
Work From Abroad Program allowing up to 40 days of work outside your contracting country
We celebrate diversity as one of core values, join and drive one of the c‑a‑r‑e initiatives together with us!
TeamViewer is an equal opportunities employer and is committed to building an inclusive culture where everyone feels welcome and supported. We C‑A‑R‑E and understand that our diverse, values‑driven culture makes us stronger. As we continue to grow as a company, we also focus on enabling our employees to grow both personally and professionally. We are proud to have an open and embracing workplace environment that will empower you to be your best no matter your gender, civil or family status, sexual orientation, religion, age, disability, education level, or race.
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