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Checkout.com is a global fintech platform powering over 10 billion transactions yearly for companies like eBay, Spotify, Klarna, and Uber. As Senior Data Analyst in People Analytics, you will be a senior individual contributor leading the People Analytics team's mission to enable data-driven people decisions across the organization.
You will own a portfolio of stakeholder relationships and co-own the evolution of the data platform. Key responsibilities include:
Data Ecosystem Quality: Lead continuous improvement of the People Analytics data ecosystem—pipeline quality, semantic layer, and data products shared across teams. Bring data engineering rigor to ensure reliability, documentation, and readiness for AI-driven products.
End-to-End Product Development: Own the full lifecycle for assigned stakeholder groups—from requirements gathering and design through pipeline development, Looker delivery, and enablement. Serve as primary People Analytics partner for Business Partnering and Finance teams.
Machine Learning & AI: Design, build, and deploy ML models and AI-powered data products. Identify high-value use cases and deliver production-grade solutions using the cloud-native stack, from predictive people models to intelligent data applications.
Advanced Analytics: Conduct analyses explaining why patterns occur and anticipating future trends. Partner with the People Analytics Manager on complex, strategically important questions.
Enablement: Drive data fluency across stakeholder groups through demos, documentation, training, and self-service tooling.
Growth opportunities include expanding product ownership to additional stakeholder groups, building increasingly sophisticated AI products, and moving into consultative work shaping how senior leaders interpret people data.
Essential qualifications: significant experience as data analyst or analytics engineer in established data engineering teams; strong SQL with BigQuery or comparable cloud warehouse experience; hands-on pipeline building with dbt or equivalent; end-to-end dashboard and data product development in Looker; excellent communication translating complex data for non-technical audiences; collaborative, enablement-focused mindset.
Desirable: production ML or statistical modeling experience; AI product development or LLM tooling exposure; data quality frameworks, semantic layers, or observability tooling; prior HR, people, or workforce data experience.
Checkout.com operates a hybrid model with three days per week in-office to support collaboration. The company emphasizes real ownership, meaningful challenges, and growth opportunities for high performers.
