WHAT YOU BRING

• 3+ years of experience in data analysis, ideally within fintech or financial services.
• A degree in Data Science, Statistics, Finance, Computer Science, or a related field.
• Proficiency in SQL and modern data visualization tools (e.g. Omni, Power BI, Looker, Tableau).
• Familiarity with Python or R for data analysis and automation is a plus.
• Strong analytical and problem-solving skills, with the ability to distill complexity into actionable insights.
• Excellent communication skills. You are able to translate data into narratives for both technical and non-technical audiences.

ABOUT US

We are LIQID, one of the fastest-growing fintechs in Europe. Our purpose is to provide creators, entrepreneurs, and thinkers shaping our future with access to the same opportunities as the world’s most successful investors while balancing the demands of people, planet, and profit.
We offer our clients financial peace of mind through exceptional, curated investment solutions – ranging from the world’s best private equity and venture funds to award-winning wealth management solutions. All delivered via an intuitive digital experience with outstanding personal support. With over €3 billion in assets, we are backed by leading investors from the digital, private equity, and wealth management space, including LGT, Toscafund, HQ Trust, and Project A.

YOUR ROLE

We are looking for a Data Analyst to join our growing data team and help transform complex datasets into clear, actionable insights. You’ll collaborate closely with teams across finance, product, engineering, and marketing to uncover trends, optimize performance, and empower decision-making through data.Your work will play a key role in building a data-driven culture at LIQID by enabling better visibility, stronger reporting frameworks, and easier access to trustworthy metrics.

WHAT YOU WILL DO

• Translate complex data into clear insights that support strategic and operational decisions across the business.
• Design, build, and maintain dashboards and reports to track key performance indicators and business metrics.
• Collaborate with stakeholders from finance, product, engineering, and marketing to understand data needs and identify gaps.
• Improve data accessibility through scalable reporting frameworks and self-service capabilities.
• Contribute to a shared understanding of metrics by helping standardize definitions and ensuring data integrity.