Junior Analytics Engineer

About the role

This role is centered on Looker within a high-scale analytics environment where data drives product and business decisions. You will own one of the most widely used pieces of Preply's analytics ecosystem, ensuring that more than 900 people across the company can easily find, understand, and trust the data they use every day. The position is hands-on from day one, combining analytics engineering, data governance, documentation, and continuous improvement of the self-service analytics platform. You will partner closely with Product, Growth, Finance, Engineering, and AI teams to support hundreds of A/B tests, a complex two-sided marketplace, and AI-driven personalization. This is a role where your work directly impacts how quickly teams can make confident, data-backed decisions at a global scale.

Key facts

What you'll do

• Own Looker licensing by managing the license granting process, acting as the point of contact with Looker's service, staying up-to-date with new Looker upgrades, identifying unused licenses, and periodically revoking them to optimize cost and access.
• Classify and organize Looker artifacts to establish clear structure and governance, ensuring consistent reflection of this structure across Looker for discoverability and reliability.
• Create and maintain high-quality technical documentation, user guides, and onboarding materials that help teams work confidently with data and understand core concepts.
• Support continuous improvement by identifying opportunities, proposing improvements, and running lightweight innovations to test new ideas for analytics workflows and tooling.
• Partner with stakeholders across the business to be the go-to person for Looker, helping teams find, understand, and use data effectively in their day-to-day work.
• Work directly with data to write and explore queries using SQL, enabling you to validate metrics, troubleshoot issues, and support data-driven discussions.
• Collaborate with data analysts and data scientists to translate business requirements into analytics models, ensuring that metrics are well defined and aligned with business goals.
• Contribute to the stability and scalability of the analytics platform by maintaining Looker views, explores, and dashboards with attention to performance and clarity.
• Promote data governance by enforcing naming conventions, access controls, and documentation standards that make the analytics ecosystem more maintainable.
• Act as a bridge between technical implementations and business users, translating complex data concepts into understandable insights and training materials.
• Identify patterns in data usage to optimize Looker instance performance, reduce redundancy, and improve the overall user experience for internal teams.
• Support the evaluation and adoption of new Looker features, testing upgrades and providing feedback to ensure they meet the needs of diverse user groups.
• Maintain strong relationships with internal customers, gathering feedback on analytics usability and driving improvements that increase trust in data.
• Ensure that documentation stays current with platform changes, enabling new team members to ramp up quickly and reducing dependency on specific individuals.
• Contribute to long-term platform strategy by sharing best practices and advocating for standards that enhance consistency across analytics products.

Requirements

• Working knowledge of SQL and confidence querying and exploring data to support analysis and validation tasks.
• Understanding of business metrics and how data supports product and business decisions in a fast-paced, growth-oriented environment.
• An analytical mindset where you enjoy understanding what data means, not just retrieving it, and you care about accuracy and clarity.
• Strong attention to detail and an interest in making data organized, reliable, and easy to discover for a large internal audience.
• Hands-on experience through internships, industry projects, or relevant personal projects that demonstrate your engagement with real-world data challenges.
• Commercial experience is a plus, showing that you can operate effectively in a business context and understand stakeholder needs.
• Comfortable using AI tools to improve productivity and accelerate your learning in analytics and data engineering domains.
• English proficiency at B2 level or above to communicate clearly with global teams and produce high-quality documentation.

Practical notes

Our principles guide how we work and how we grow. Care to change the world reflects our passion for impact and our commitment to meaningful change. We do it for learners, keeping their success at the center of every decision we make. Keep perfecting drives us to simplify, smooth experiences, and refine details continuously. Now is the time pushes us to act quickly in a fast-paced environment and deliver results when it matters. Disciplined execution ensures that we set clear goals, focus on what matters, and use our resources efficiently to achieve our objectives. Dive deep encourages us to investigate disparities between numbers and stories, unlocking insights that guide smart decisions. Growth mindset means we seek growth opportunities and believe today's best performance becomes tomorrow's starting point, fostering continuous development for ourselves and the products we build.