Join our global force of 400+ innovators, blending the latest in tech with the greatest in soundtracking — from our Stockholm HQ to offices in London, New York, Los Angeles, Berlin, Paris, Oslo, and Seoul. We're an industry leader with a startup mentality. We take what we do seriously, but we don't take ourselves too seriously. Come create with us, and let the world feel your work.
As a Senior Data Analyst, you'll join an embedded, AI-native analytics team that sits inside the commercial and product domains driving our growth. You'll work shoulder-to-shoulder with the VP of Revenue Operations and Global Sales Leadership as we scale our enterprise business — defining what success looks like across the full bow-tie funnel, from pipeline generation to expansion revenue, and proving it with data. You'll have a dedicated mandate within the Enterprise GTM org while drawing on the shared infrastructure, engineering support, and peers of our central Data & Analytics team.
Partner with RevOps and Sales leadership to define success metrics, surface growth opportunities across the enterprise bow-tie funnel, and shape GTM strategy with evidence — proactively raising the questions stakeholders haven't thought to ask.
Build and refine the models that steer the business — customer segmentation for territory and capacity planning, lead and account scoring for pipeline quality, and forecasting for pipeline and revenue.
Make our data trustworthy for agentic analytics — enrich context and metadata, and use AI coding tools to ship instrumentation and data-quality fixes directly so both people and AI tools can rely on it.
Own the analytical backbone of how the enterprise business is steered — KPI and metric definitions aligned across Sales, Marketing, and Finance, and the monthly, quarterly, and annual performance forums, owning the narrative, not just the slides.
Close data gaps and build scalable, self-serve measurement infrastructure so GTM teams can monitor long-term performance without you in the loop.
Uphold rigor as self-serve expands — push back on false precision in pipeline and forecast numbers, set the bar for what good analysis looks like, and resist sophistication, statistical or AI, where a simpler approach serves the decision better.
Senior-level influence. You've driven real business impact by shaping decisions at the leadership level and moving revenue outcomes.
High agency. Habit of driving decisions through tailored communication and data storytelling.
Sharp analytical instincts. You scope vague questions with vetted frameworks, state hypotheses up front, and reason to a defensible answer even with imperfect data.
Sound judgement about data. A solid grasp of statistics and the discernment to know when past data predicts the future and when to override it for where the business is heading.
Technical versatility. Proficiency across SQL and Python (notebooks in Hex), dbt (on BigQuery), plus experience with AI coding tools and techniques including context engineering and evals.
PLG/SaaS fluency. Hands-on experience in product-led and SaaS businesses, with a solid grasp of subscription economics and the metrics that drive them.
Experience across the B2B GTM funnel — Sales, Marketing, and RevOps — with funnel, segmentation, and forecasting analytics.
Data modelling know-how and experience with semantic layers.
A track record of defining metrics and steering frameworks for enterprise or 0 1 commercial motions.
A fast-paced environment with real room for personal growth and tangible impact on the business.
The chance to help write the new playbook for running Analytics in the AI era, combining timeless principles with fresh learnings from emerging tooling.
A diverse, collaborative team of Analysts and Engineers building together.
We believe that bringing people together from different backgrounds, experiences and perspectives makes for a healthy workplace, a more successful business and a better world. We value diversity and encourage everyone to come and soundtrack the world with us.
Ready to make the world feel your work? Please apply, in English.
