Senior SQL Data Analyst in London

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. 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. 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.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. Job responsibilitiesData ecosystem quality: Lead the continuous improvement of the People Analytics data ecosystem — including pipeline quality, semantic layer, and the data products we share with other teams. You will bring the rigour of an established data engineering team to our stack, ensuring our data is reliable, well-documented, and ready to power AI-driven products. Machine learning and AI: Design, build, and deploy ML models and AI-powered data products. Working from our People Analytics AI roadmap, you will identify high-value use cases and deliver production-grade solutions — from predictive people models to intelligent data applications — using our cloud-native stack. Conduct analyses that go beyond what happened to explain why and anticipate what comes next. Drive data fluency across your stakeholder groups through demos, documentation, training, and self-service tooling. Make data accessible, not just available. Build increasingly sophisticated AI products — from predictive models to deployed data applications used across the businessStrategic influence: Move further into consultative and diagnostic work, shaping how senior leaders interpret and act on people dataKey requirementsEssential: Significant experience as a data analyst or analytics engineer in a team with established data engineering practicesStrong SQL, with hands-on experience in BigQuery or a comparable cloud data warehouseExperience building and maintaining data pipelines with dbt or a comparable transformation toolExperience building dashboards and data products end-to-end for business stakeholders, ideally in LookerExcellent communication skills — able to translate complex data into clear, actionable insights for non-technical audiencesCollaborative, enablement-focused mindset: you build for self-service, not dependencyDesirable: Experience with machine learning or statistical modelling in a production contextExposure to AI product development, LLM tooling, or data applicationsExperience with data quality frameworks, semantic layers, or data observability toolingPrior experience working with HR, people, or workforce dataAdditional InformationBring all of you to workWe create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.