Senior Data Analyst, People Analytics
Role Summary
Join Checkout.com as a Senior Data Analyst in London, focusing on innovative people analytics, machine learning, and AI-driven products.
About the Organisation
We’re Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day.
We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers.
Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale.
If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact.
With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started.
As a Senior People Data Analyst, you will play a leading role in the People Analytics team at Checkout.com. Our mission is to enable data-driven people decisions across the organisation — from the executive team to individual managers.
You will combine deep analytics engineering experience with end-to-end product ownership: bringing the technical discipline to raise the quality of our data ecosystem, the stakeholder instincts to deliver products that people actually use, and the curiosity to push the boundary of what People Analytics can do through machine learning and AI.
This is a senior individual contributor role with real scope. You will own a portfolio of stakeholder relationships, co-own the evolution of our data platform, and contribute to one of the most ambitious People Analytics strategies in the business.
Minimum Requirements
- Significant experience as a data analyst or analytics engineer in a team with established data engineering practices
- Strong SQL, with hands-on experience in BigQuery or a comparable cloud data warehouse
- Experience building and maintaining data pipelines with dbt or a comparable transformation tool
- Experience building dashboards and data products end-to-end for business stakeholders, ideally in Looker
- Excellent communication skills — able to translate complex data into clear, actionable insights for non-technical audiences
- Collaborative, enablement-focused mindset: you build for self-service, not dependency
- Experience with machine learning or statistical modelling in a production context
- Exposure to AI product development, LLM tooling, or data applications
- Experience with data quality frameworks, semantic layers, or data observability tooling
- Prior experience working with HR, people, or workforce data
Eligibility Criteria
Eligibility details are not specified; applicants should verify work authorization requirements.
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