data analyst in People Analytics

Checkout.com provides payment technology that powers digital experiences and enables billions of transactions for global shoppers and businesses. Its platform supports online payments at scale, and the company operates in the fintech sector.

• Lead continuous improvement of the People Analytics data ecosystem, including pipeline quality, semantic layers, and shared data products;
• Own the full product development lifecycle for assigned stakeholder groups, from requirements gathering and design to pipeline development, Looker delivery, and enablement;
• Support existing products and deliver new products for Business Partnering and Finance;
• Design, build, and deploy ML models and AI-powered data products;
• Identify high-value use cases from the People Analytics AI roadmap and deliver production-grade solutions;
• Conduct advanced analyses to explain drivers and anticipate future outcomes;
• Partner with the People Analytics Manager and senior stakeholders on complex and strategically important questions;
• Drive data fluency through demos, documentation, training, and self-service tooling.

• Significant experience as a data analyst or analytics engineer in a team with established data engineering practices;
• Strong SQL and hands-on experience with 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 for translating complex data into clear, actionable insights for non-technical audiences;
• Collaborative, enablement-focused mindset with a focus on self-service;
• Nice to have: 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.

• Three days per week in the office;
• The role offers ownership, meaningful challenges, impact recognition, and growth opportunities.