Senior Analytics Engineer

About the role

We’ve signed up to an ambitious journey. Join us!

As Arrive, we guide customers and communities towards brighter futures and more livable cities, it isn’t a challenge just anyone could take on. Luckily, we have something to help us make it happen. Our people and our values. We Arrive Curious, Focused and Together. Just as our entire brand is inspired by the North Star, the shining light leading travelers to their destinations since time began, our values guide us. They help us be at our best. For our customers. For the cities and communities we serve. For ourselves. As a global team, we are transforming urban mobility. Let’s grow better, together.

An exciting hybrid working opportunity has arisen for a talented and driven Senior Analytics Engineer within our YourParkingSpace business in London (SE1).

The Role

As a Senior Analytics Engineer, you'll play a critical role in shaping and driving the data strategy that powers our analytics, products and commercial decision-making. Beyond building and maintaining robust data infrastructure, you'll act as the bridge between technical delivery and business outcomes, ensuring our data capabilities are aligned with commercial priorities and that stakeholders across the business can confidently rely on data to inform their decisions.

This is a hands-on senior-level role where you'll own data pipelines end to end, from ingesting raw data from multiple sources to transforming and delivering high-quality, analytics-ready datasets. You'll also contribute to the data roadmap, working closely with business stakeholders to understand their needs, prioritise work that delivers the most value, and clearly communicate progress and technical trade-offs.

How to make an impact

- Design, build and maintain end-to-end data pipelines, including ingestion, transformation and delivery of data to analytics and reporting layers.

- Own and improve existing data pipelines, ensuring high reliability, performance and scalability.

- Set up new pipelines for internal and external data sources, selecting appropriate tools and patterns.

- Monitor data quality, accuracy and pipeline health, proactively identifying and resolving issues to ensure high levels of data trust and uptime.

- Implement analytics engineering best practices, including testing, documentation, version control and observability.

- Continuously improve data architecture, modelling and workflows to support growing data volumes and evolving business needs.

- Partner with commercial, product and operational stakeholders to understand their data needs and translate business questions into well-scoped analytics engineering solutions.

- Help shape and prioritise the analytics engineering backlog, balancing technical improvements with high-impact business requirements.

- Define and communicate the data scope for new initiatives, providing clear assessments of feasibility, effort and expected value.