Analytics Engineer

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Company Description

We’re  – you might not know our name, but companies like eBay, ASOS, Klarna, Uber Eats, and Sony use our service. That moment when you check out online? We make it happen.  powers billions of transactions every year, enabling digital payments to work smoothly so businesses grow and customers stay. With 19 offices on six continents and London as our HQ, we’re fast‑moving, performance‑obsessed, and driven to be better each day.

A role here is a career‑defining opportunity to build the future of fintech.

As a Data Analytics Engineer at Checkout you will enable key insights on how products perform and establish a single source of truth for North Star and tracking metrics. Working closely with product managers and data scientists, you will shape the product’s evolution, build new data products, and introduce step‑changes in how we view analytics for critical areas. You will own multiple data products from design to implementation to operationalisation.

• Design and implement high‑performance, reusable, and scalable data models for our data warehouse using dbt and Snowflake
• Design and implement Looker structures (explores, views, etc.) which enable users across the organization to self‑serve analytics
• Work closely with data analysts and business teams to understand requirements and provide data ready for analysis and reporting
• Continuously discover, transform, test, deploy and document data sources and models
• Apply, help define, and champion data warehouse governance: data quality, testing, documentation, coding best practices and peer reviews
• Take initiative to improve and optimise analytics engineering workflows and platforms

• Proven delivery experience as a data, business intelligence or analytics engineer
• Hands‑on proven data modeling and warehousing skills demonstrated in large‑scale data environments
• Proven experience in software development lifecycle in analytics (e.g. version control, testing, and CI/CD)
• Excellent SQL and data transformation skills (ideally proficient in dbt or similar)
• Familiarity with at least one of:
  Snowflake, AWS, Google Cloud, Microsoft Azure
• Passionate about sales, finance, customer, marketing and/or product analytics data
• Good attention to detail to highlight and address data quality issues

We create conditions for high performers to thrive – real ownership, fewer blockers, and work that makes a difference from day one. Here you’ll move fast, take on meaningful challenges, and be recognised for the impact you deliver. We work as one team, backing each other to succeed, and you’ll find yourself freed to grow. We also offer a hybrid working model: three days per week in the office to support collaboration and connection.

Entry level

Full‑time

Information Technology