Data Analyst

Sibill is the accounting and financial operating system for small and medium businesses (SMBs). Outdated tools and fragmented data waste entrepreneurs a lot of hours each week — we give this time back by integrating invoicing, payments, treasury, and accounting in one modern platform.
We’re backed by top international investors such as Keen Venture Partners (Fiscozen), Founders A/S (Pleo), Exor Ventures (Qonto, Alan), Notion Capital, and most recently Creandum, known for supporting Klarna and Spotify at early stages.

Thousands of entrepreneurs already trust Sibill.

Our goal? Reach millions. This is just the beginning.

What we look for

We are looking for a motivated, pragmatic, and goal-oriented Data Analyst to join our Data team.

You are the perfect fit if...

• You are passionate about technology, statistics and business. The three of them.

• You don’t feel “done” yet, you want to keep learning and applying science to drive business outcome. You still want to be hands-on.

• You are excited about working in a flat, no-politics, fast-paced environment.

• You have excellent analytical skills and and a sharp eye for detail.

• You are not scared of working hard. As a team, we all have to go the extra-mile to make it happen.

• You feel like fitting the values we share at Sibill: ambition, pragmatism, efficiency, integrity

What you will do

You will report to our Senior Data Engineer. You will work with her and build all the data pipelines and metrics that empower our team with business intelligence and analytics. This will not be a one-man standing. It will take a lot of cross-functional work with the people in our data, product, marketing, customer success, sales teams.

We sit on top of the most business-critical company data. Money flows, bank transactions, invoices, cash register records, payables and receivables, general ledger records. We are the accounting & finance operating system of our customers. We couple this with a vast amount of user behavior, CRM, billing data we ingest in our warehouse. There are limitless possibilities when it comes to what data we have available. The scarce resources are focus and insights.

Your responsibilities will include:

• Discovery, domain understanding, data collection and experimentation

• Solving a data need end-to-end. Understand the data source, write the data pipeline, run the analysis, build the visualization

• Monitoring of and iteration over existing data pipelines & metrics

Examples of projects you could work on from month one at Sibill:

• Build a data pipeline that collects net promoter score (NPS) ratings from our survey tool, ingests in our analytics data warehouse and enriches our CRM. Then, analyze how NPS changes over time across customer industry, size, price point and add NPS change to the set of features used for churn prevention modelling.

• Analyze the adoption of core features within our customer base and find patterns that help us identifying upsell opportunities.

• Track funnel performance (website visit → form submission → qualification → demo → purchase) across different lead attributes and source split. Find room for optimization within our marketing flows and sales processes.

What you will need

• B.Sc./M.Sc. in Data Science, Statistics, Computer Science, Mathematics or a related STEM field. You won’t be asked to send rockets to Mars - but a solid background in stats will give you an edge.

• At least 2 years of hands-on experience.

• Modern Python skills. You might need it to build data pipelines and automation tasks.

• Advanced SQL proficiency. Ability to write complex, structured pipelines (CTEs, temp tables, window functions, etc). Query optimization techniques and relational database concepts will help you move faster and deliver stronger pipelines.

• Proven expertise in delivering analyses and data visualizations that make sense to both technical and non-technical audiences.

• Effective, clear, transparent communications.

• Especially at the beginning, an end-to-end data ownership mindset. It will not happen every day but - if necessary - you might be asked to build your own data pipeline end-to-end, to write a batch ETL, to write Python code, or to support teammates with an important one-off empirical analysis in Excel.

• Fluency in English and Italian.

Comp & Benefits

• RAL: 30-40k

• Lunch voucher (8€/business day)

• Full remote (based in Italy). We will just ask you to come to Milan for a few weeks during the onboarding. If you are based in Milan, more than happy to welcome you at the office every day.

• You will work within a team of smart, hard-working, passionate and nice human beings. People in Sibill tend to be very happy. Happiness is an underrated benefit ;)

Recruiting process

1. a quick chat with Gaia, our HR Manager

2. 30 minutes “know-each-other” session with Isabella (Data Engineer)

3. 45 minutes technical interview

4. 45 minutes with Dario (Chief Data Officer)