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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 Lead BI Engineer based in our YourParkingSpace business in London (SE1).

The Role

As a Lead BI 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 that 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 lead 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 have an important role in contributing to the data roadmap, working closely with business stakeholders to understand their needs, prioritise work that drives the most value, and communicate progress and trade-offs clearly.

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 data trust and uptime.

• Implement best practices for BI engineering, including testing, documentation, version control, and observability.

• Continuously improve data architecture and workflows to support growing data volumes and evolving business needs.

• Partner with commercial, product, and operational stakeholders to understand their data needs, translating business questions into well-scoped BI engineering work.

• Help shape and prioritise the BI engineering backlog, balancing technical improvements with high-impact business requests.

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

Your background

• 5+ years’ experience in a BI / Data engineering role. with at least 2 years operating in a lead or senior capacity where you've influenced priorities beyond your immediate team.

• Strong Python skills, with experience building ELT/ETL pipelines.

• Strong SQL skills, with experience building and optimizing complex transformations.

• Experience developing data pipelines using modern data stack tools (e.g. ELT/ETL frameworks, cloud data warehouses, orchestration tools).

• A Degree in Computer Science, Engineering, Mathematics, Statistics, Economics or another quantitative field (or equivalent work experience).

• Solid understanding of data modelling concepts and analytics-ready schemas.

• Demonstrated experience managing relationships with business stakeholders, including scoping data requirements, setting expectations, and delivering against commercial priorities.

• Commercially minded: you understand how data supports revenue, operations, and strategic goals, and you use that understanding to guide where you invest your effort.

• Strong communication skills, with the ability to explain technical concepts and trade-offs to non-technical audiences.

This role is hybrid role based in London (SE1), 3 days in the office per week, 2 days from home.