Analytics Engineer

💙 About Bounce...

Bounce is a global luggage storage marketplace transforming the way people travel and explore. With over 20,000+ trusted partners in 100+ countries, Bounce connects travelers with local businesses offering secure, on-demand storage solutions - letting travelers experience cities freely, without being weighed down by their things. We have over 2 million active customers relying on Bounce to simplify their journeys, offering them the flexibility to focus on what matters most, the freedom to explore.

To achieve this, Bounce is a fast-paced and scrappy team. We believe that experimentation fuels innovation, so we move quickly, testing new ideas and adapting in real time. If you’re ready to make an impact in a high-energy, close-knit, and collaborative environment - Bounce is the place where you can move fast, think big, and shape the future of travel. Join us as we make the world a lighter, more accessible place! Bounce has been named the Inc5000’s fastest-growing travel company in the USA in 2024 and is proudly backed by leading Silicon Valley investors, including Andreessen Horowitz, General Catalyst, and Sapphire. (Learn more about Bounce's Series B HERE and also learn about our Japan Expansion HERE)

About the role...

Bounce is seeking an Analytics Engineer to join our Lisbon office. This role will play a pivotal part in scaling our business operations and product development by making data more accessible, reliable, and actionable across the company.

You’ll work closely with cross-functional teams and stakeholders to model data, define metrics, build reusable assets, and develop intuitive experiences around data. You’ll help drive a culture of self-serve, ensuring that teams across Bounce can make informed decisions without friction.

We’re building a modern, developer-friendly data stack focused on semantic modeling and AI-native self-serve analytics, with tools like dbt, Dagster, Cube, and Hex. You'll not only help shape and evolve this stack—you'll also play a key role in teaching others how to use it and contribute to it. Expect to lead internal enablement, documentation, and tooling improvements that make the stack approachable for the whole company.

What do you need to bring to the table? Strong experience in analytics engineering, a product mindset, and a desire to make data a first-class citizen across the org. You should be excited about creating systems that scale and simplifying complexity for others.

We’re looking for a generalist who thrives in a fast-paced environment and enjoys owning outcomes from beginning to end.

Where you come in...

• Partner with data science, product development, and business stakeholders. Dive deep into their data needs, decode their language, and transform these insights into infrastructure and tooling that enables a data-driven culture.
• Unleash the power of data to monitor and track the beating heart of our operations. Create eye-catching dashboards that serve as our compass, craft strategies for expansion, and wield your forecasting skills like a seasoned fortune teller.
• Be the detective who spots the gaps in our product analytics data. Join forces with our brilliant engineering squads to enhance product data tracking and attribution, ensuring we have the clearest picture of what's happening.
• Create robust testing and monitoring systems that stand as guardians of data quality and build documentation that paves the way for data accessibility to every stakeholder.
• Roll up your sleeves and contribute to the evolution of our analytics pipelines. Introduce automation wherever it makes sense, breathing new life into our data pipelines and analyses.
• Lead the cause of data and data-driven decisions. Be the champion who empowers informed choices throughout our organization.
• Be an owner, taking a personal stake in the success of the product and the team.

Your profile...

• Degree in a quantitative field such as statistics, economics or engineering, or relevant work experience
• 2+ years of industry experience in a similar role
• Advanced proficiency in SQL and Python
• Experience with ETL/ELT tools such as dbt
• Experience with data visualization tools such as Amplitude, Hex, or similar
• Knowledge of data warehousing concepts, big data technologies, and analytics platforms.
• Strong oral and written communication skills and ability to collaborate with and influence cross-functional partners
• Avid learner and practical problem solver
• Professional proficiency in English, written and spoken