Senior Data Analyst - Enterprise GTM
RemoteStockholm, Stockholm, Sweden
Job Summary
Senior Data Analyst for Enterprise GTM leading analytics within the commercial/product domain. Embed with RevOps and Global Sales leadership to define success metrics across the enterprise bow-tie funnel, build and refine models for territory planning, lead and account scoring, and forecasting; ensure data trust and self-serve instrumentation; define KPI and metric definitions across Sales, Marketing, and Finance; drive scalable analytics infrastructure and self-serve capabilities; operate in a fast-paced, AI-enabled analytics environment with a focus on data-driven growth for enterprise SaaS. Requires senior-level influence, strong data storytelling, and technical proficiency in SQL, Python, dbt on BigQuery, and familiarity with AI tooling and subscription economics.
Required Qualifications
- Senior-level influence
- High agency
- Sharp analytical instincts
- Sound judgement about data
- Technical versatility across SQL and Python (notebooks in Hex)
- dbt on BigQuery
- Experience with AI coding tools and context engineering/evals
- PLG/SaaS fluency in product-led and SaaS businesses
- Experience across B2B GTM funnel (Sales, Marketing, RevOps)
- Data modeling and semantic layers
- Track record of defining metrics and steering frameworks for enterprise or 0→1 motions
Desired Qualifications
- Senior-level influence with leadership exposure
- Strong stakeholder-management and data storytelling skills
- Advanced SQL and Python proficiency (notebooks in Hex)
- dbt experience on BigQuery
- Experience with AI coding tools and techniques including context engineering and evals
- PLG/SaaS fluency and understanding of subscription economics
- Ability to define and align KPI/metrics across Sales, Marketing, and Finance
- Experience building scalable self-serve analytics infrastructure
- Strong problem-solving with a data-driven mindset
- Experience partnering with RevOps and Sales leadership
- Ability to ship instrumentation and data-quality improvements
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