Product Data Analyst

Pillar; Lombardia; On-site; EUR 40,000 - 50,000; Full time

Benefits offered by this job

Gross salary 40-50k €

€2k welfare budget and meal vouchers

Job summary

Pillar in Italy is seeking a Product Data Analyst who loves turning messy data into clear decisions. You’ll partner with product, CS and sales to define goals, ensure data is tracked before features ship, and help create a trusted single source of truth.

You’ll work with SQL, Python and BI tools, build dashboards, and help forecast churn, activation and revenue. This role combines hands‑on analytics with product intuition in a fast‑growing fintech for construction.

Qualifications

• Fluent in SQL and Python for analysis and automation.
• Hands-on, end-to-end data work from raw data to dashboards.
• Experience with at least one BI tool and product analytics tools.
• Comfort turning data into actionable insights for SaaS metrics.

Responsibilities

• Shape goals and KPIs. Help the Product team define goals, success metrics and how to track them over time.
• Make sure the data exists. Work with Engineering on tracking requirements so data is ready before a feature ships.
• Build one source of truth. Create shared dashboards and validate AI outputs.
• Support both roadmaps. Challenge the product roadmap with data and provide insights on customers.
• Start close to Customer Success. Collaborate on health score and churn signals.
• Turn questions into answers. Analyze questions into clear reports with actionable conclusions.

Skills

SQL

Python

BI tools

Product analytics

SaaS metrics

Data storytelling

Communication

AI-native

Tools

Metabase

Looker

Tableau

PostHog

Amplitude

Mixpanel

Job description

Pillar was founded in 2025. Today we are 80+ people, we serve 1000+ customers, we raised €12 million in 2026 and we are expanding internationally.

We are building the financial operating system for construction: bringing AI, automation and modern software to a huge industry that still runs on slow, fragmented processes.

We are looking for a Product Data Analyst who loves getting their hands dirty with data and helping the people around them make better decisions with it.

Why this role, why now

Our data is growing as fast as our customer base. Invoices, cash flows, job sites, payments: every day thousands of construction companies trust us with the numbers that run their business.

You’ll help us agree on what we measure, how we measure it and where the truth lives, so that every team can move fast and trust what they see.

The mission

Be the data partner our product teams can count on. You won't be the one making business decisions, but you will make sure every decision is built on data that is reliable, shared and easy to understand.

What you will do

• Shape goals and KPIs. Help the Product team define goals, success metrics and how to track them over time.
• Make sure the data exists. Work with Engineering on tracking requirements, so the data we need is there before a feature ships, not after.
• Build one source of truth. Create shared dashboards everyone can rely on, and bring a healthy double check to what AI tools generate.
• Support both roadmaps. Challenge the day-to-day product roadmap with data, and support bigger strategic bets with insights on our customer base: who they are, how big they are, public or private work, tenders.
• Start close to Customer Success. In your first months you'll work closely with CS on our customer health score (usage, CS sentiment, ICP fit), back-test it on churned customers and help find the signals that predict churn early.
• Turn questions into answers. Take questions from Product, Customer Success, Sales and leadership and turn them into clear analyses with a concrete "so what".

What this role is not

• Not a dashboard factory. A dashboard nobody opens is not a product. If it doesn't help a decision, we don't build it.
• Not data science. A separate team works on data pipelines, invoices and the Pillar price list. You'll work closely with them, but your focus is product and customer analytics.
• Not waiting for the perfect dataset. When an event is missing or a question is fuzzy, part of the job is figuring out what data we need and how to get it.
• Not a service desk. You're in the room with the people who decide, and we expect you to have opinions.

Who we are looking for

• 3 to 5 years in product or data analytics in a SaaS startup or scaleup.
• Fluent in SQL. This one is non-negotiable. Python for analysis and automation is a big plus.
• Hands-on, end to end. From raw data to the final dashboard. Raw tables, JSON and messy databases don't scare you, and you can get what you need without a dedicated data engineer.
• Tool-savvy. Experience with at least one BI tool (Metabase, Looker, Tableau or similar). Product analytics tools like PostHog, Amplitude or Mixpanel are a plus.
• At home with SaaS metrics: activation, adoption, retention, churn, expansion, and how they connect to revenue.
• Proactive by nature. You solve problems on your own, and when something is missing you go and find it.
• A clear communicator. You can explain a complex analysis to an engineer and to a construction company owner.
• AI-native. AI is already part of how you work, and you know when to double check what it tells you.
• Languages: native Italian or Spanish, plus professional working English.
• Nice to have: experience in fintech, B2B or vertical SaaS, or a curiosity for construction.

How we work

• Small squads, high autonomy, no unnecessary layers.
• AI-first, in the product and in the way we work.
• Bottom-up: initiative is expected, not delegated.
• We are direct, we give context instead of micromanagement, and we prefer an honest truth to an optimistic slide.

Pillar may not be the right place if you need a fully defined scope or a mature data team around you from day one. Here, you help build it.

What we offer

• Gross salary 40-50k €.
• [For Italy] €2k welfare budget and fringe benefits and meal vouchers (8 €/day).
• The chance to shape Pillar's data culture as we scale.
• Real ownership, with direct exposure to customers, founders and leadership.
• An AI-native team where you can grow as fast as the company does.

Hiring process

01 CV screening.

02 30-min call with People.

03 60-min Technical interviewwithour Senior Data Analyst: SQL, data modelling and how you reason through a problem and Live Case study (a real data problem from our world)

04 Final conversation with our co-founder and CTO, to get to know each other better.