We're looking for an experienced and strategic Senior Data Analyst to join Uberall's product team. In this role, you’ll be at the heart of product decision-making, working closely with product managers on how we measure each product, whether launches work, and what the data tells us. Your skills in distilling complex data into meaningful narratives will be instrumental in supporting our growth and product innovation.

If you’re passionate about using data to tell compelling stories, enjoy structuring insights that influence product decisions, and thrive in a collaborative environment, this could be the perfect role for you. Join us in creating exceptional experiences for our clients and helping shape the future of our products. Apply today to make a tangible impact with your data expertise!

Your Responsibilities:

• Build and maintain well-documented product data models in dbt, working within the BI team's shared standards and review process.

• Act as the analytics point of contact for the Product data domain, working with domain owners and data partners to keep metric definitions and standards consistent across the company.

• Build and maintain dashboards and reports that give product managers a clear, self-serve view of how their products are performing.

• Define and monitor key product performance metrics with stakeholders, focusing on areas such as acquisition, retention, monetization, and adoption to drive product and business insights.

• Collaborate with product managers, engineers, and cross-functional teams to prioritize features and drive a data-informed product roadmap.

• Create clear, concise stories from data analyses, presenting findings to technical and non-technical audiences to inform product decisions and strategy.

• Conduct in-depth analyses of user behavior, feature usage, and A/B test results to evaluate product changes and measure their impact on user engagement, retention, and revenue.

• Analyze product usage trends to define activation metrics that increase customer lifetime value (LTV), and contribute product usage signals to churn prediction alongside data and Customer Success partners.

• Shape the product analytics roadmap together with product managers, prioritizing the questions that matter most for each product area.

• Mentor and support team members, promoting best practices in data analysis and effective communication across the organization.

• Use AI-powered analytics tools and agentic workflows (LLM assistants, automations, AI product tracking) on top of our shared data platform to scale self-serve insights for product teams.

Your Profile:

• 5+ years of experience in data analysis, ideally with experience in or close collaboration with product teams in a SaaS or technology environment.

• Advanced skills in BI and product analytics tools (e.g. Metabase, Pendo), and comfortable picking the right tool for each question.

• Strong command of SQL, with the ability to create and optimize complex queries on large datasets.

• Solid experience in data modelling (e.g. dimensional modelling, dbt or similar), designing clean, documented and reusable models that act as the single source of truth for product metrics.

• Hands-on experience using AI tools (e.g. coding assistants, LLM-powered analytics) to accelerate query and model development, automate repetitive work and speed up insight generation, while keeping a critical eye on accuracy.

• Proven ability to translate complex data insights into clear, actionable recommendations for cross-functional teams.

• Hands-on experience with adoption analysis, A/B testing frameworks and statistical analysis, with a solid foundation in designing and analyzing experiments.

• Proven experience in establishing and tracking core product metrics and driving insights that influence product development and growth initiatives.

• Exceptional communication and presentation skills, adept at engaging and aligning stakeholders at all levels.

• Highly organized, with strong prioritization skills to manage multiple projects and deadlines.

• Comfortable working both independently and collaboratively in a dynamic, fast-paced environment.

• Fluency in English is required; additional language skills are a plus.