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Salary: EUR 40,000 - 50,000 / annual
Pillar is a financial operating system for construction, founded in 2025 and now 80+ people serving 1000+ customers. The company raised €12 million in 2026 and is expanding internationally. You will be the Product Data Analyst responsible for helping product teams make better decisions through reliable, shared, and easy-to-understand data.
In this role, you will shape goals and KPIs for the product team, defining success metrics and tracking them over time. You'll work closely with Engineering to ensure tracking requirements are met before features ship. You'll create shared dashboards that serve as a single source of truth, and bring critical review to outputs from AI tools. You'll support both day-to-day product roadmaps and strategic bets with customer insights—understanding who customers are, their size, public vs. private work, and tender participation.
In your first months, you'll partner with Customer Success to develop and back-test a customer health score based on usage, CS sentiment, and ICP fit, helping identify early churn signals. You'll translate questions from Product, Customer Success, Sales, and leadership into clear analyses with actionable insights.
This role is NOT a dashboard factory (dashboards must drive decisions), NOT data science (a separate team handles data pipelines), NOT about waiting for perfect datasets (you'll figure out what data is needed and how to get it), and NOT a service desk (you'll be in the room with decision-makers and expected to have opinions).
The company operates in small squads with high autonomy, AI-first mindset, and bottom-up initiative. You'll have direct exposure to customers, founders, and leadership, with real ownership in building Pillar's data culture as it scales.
REQUIREMENTS:
- 3 to 5 years in product or data analytics in a SaaS startup or scaleup
- Fluent in SQL (non-negotiable)
- Python for analysis and automation (strongly preferred)
- Hands-on, end-to-end capability: from raw data to final dashboard; comfortable with raw tables, JSON, and messy databases
- Experience with at least one BI tool (Metabase, Looker, Tableau, or similar)
- Product analytics tools like PostHog, Amplitude, or Mixpanel (preferred)
- Strong grasp of SaaS metrics: activation, adoption, retention, churn, expansion, and revenue connections
- Proactive problem-solver who works independently
- Clear communicator able to explain complex analyses to both engineers and non-technical stakeholders
- AI-native: comfortable using AI tools and knowing when to verify their outputs
- Native Italian or Spanish speaker, plus professional working English
- Nice to have: fintech, B2B, or vertical SaaS experience; curiosity about construction
