About Shine

Shine exists to help freelancers and small business owners reclaim the joy of working for themselves.

Running a business shouldn't mean drowning in financial admin – it should be inspiring and rewarding. Our software brings banking, invoicing, accounting and admin together in one place, so entrepreneurs can focus on what matters most: growing their business and enjoying the freedom of working for themselves.

We're a multicultural team of over 500 people across France, Germany, Denmark and the Netherlands. By bringing together leading European fintechs like Shine, Kontist and Tellow, we've built a single, intuitive platform designed for simplicity, speed and accuracy – backed by local, award-winning support.

Your hiring experience matters

Just as we respect our customers' time, we respect yours. Your experience with Shine should feel simple, transparent and genuinely supportive.

If this sounds like somewhere you want to grow, we'd love to hear from you.

Data at Shine

Our Data team is organised into three complementary pillars: Data Engineering, Analytics Engineering, and Product/Revenue Analytics. This structure ensures you spend less time fixing broken pipelines and more time uncovering high-value growth levers.

The Product Analytics team partners closely with Product to drive discovery, experimentation, and measurable impact. We are now looking for a Senior Product Data Analyst to lead the strategy for our Banking domain—the technical and financial heart of Shine’s value proposition.

What's in it for you?

• Strategic Discovery: You will lead "Phase 0" of the product lifecycle, sizing opportunities for new banking features and identifying friction points in the user journey before a single line of code is written.

• End-to-End Experimentation: From power-calculating sample sizes to interpreting complex A/B test results, you own the validation of our product hypotheses.

• High-Stakes Influence: You will translate “Data-speak” into “Business-speak,” presenting findings directly to Product Leads and the Head of Product Analytics to help the company pivot or persevere on key initiatives.

• A Mature Stack: Work with a best-in-class modern data stack including Snowflake, dbt, Python, and Omni, supported by a dedicated Analytics Engineering team.

• A hybrid work policy: Enjoy a balanced mix of remote work and office collaboration

• Modern, centrally located offices: Work from modern office spaces in prime city locations

• An international environment: Join a diverse team with colleagues from across the globe

• Mobility across locations: Opportunity to work from our offices in Copenhagen, Paris, Amsterdam, or Berlin

Your Responsibilities

• Strategic Partnership: Partner directly with Banking Product Managers to define North Star KPIs and influence the long-term roadmap.

• Deep-Dive Analysis: Lead sophisticated analyses on user activation, transaction velocity, retention, and feature adoption within the banking ecosystem.

• Data Governance: Own and continuously improve analytical datasets and core Banking KPIs, ensuring reliability, scalability, and clear documentation.

• Enablement: Build actionable, self-service dashboards and mentor junior analysts to foster a high-performance data culture.

• Best Practices: Contribute to evolving our internal analytics standards, from SQL styling to peer-review processes.

About You

• Experience: 5+ years in Data Analytics, with a proven track record in a fast-paced, product-driven environment.

• Technical Excellence: Expert-level SQL and solid experience with DBT (modeling, testing, and documentation).

• Product Mindset: You think in terms of user value and business outcomes, not just "queries completed."

• Domain Expertise: Prior experience in Banking, FinTech, or regulated environments is highly valued.

• Communication: Ability to turn complex, ambiguous problems into clear, actionable recommendations for non-technical stakeholders.

• Language: Fluent in English; excited to work in a diverse, international setting.

Our Recruitment Process

1. Screening Call: Initial screening call with a TA-partner

2. Technical Call (60’): Discussion with Saghar (Analytics Manager) + a technical SQL assessment.

3. Case Study Presentation (60’): Evaluation of your methodology, problem-structuring, and impact mindset.

4. Logical & Personality Assessment (30–45’): Followed by meeting a few team members + Discussion with the VP of Data & Analytics regarding collaboration and strategic vision.