Hello

Para presentar una candidatura, simplemente lea la siguiente descripción del puesto y asegúrese de adjuntar los documentos pertinentes.

Would you love to improve the way companies take care of their people, their most valuable asset?

We are looking for an Staff AI Analytics Engineer to join our DX and Performance team at Factorial, with a strong focus on advanced analytical architectures, semantic modeling, and integrating AI/LLM workflows into data consumption, and who want to lead that change people who:
- Think of AI as part of their engineering process, not a feature they bolt on
- Get energy from building products and seeing them generate real impact for customers
- Care more about solving complex problems than fitting a traditional job description

Ready to take on the challenge?

DX and Performance Team

The team’s primary goal is to increase Factorial’s quality, performance, and scalability by continuously improving the way we build our product. We focus on strengthening our tools, maintaining foundational elements,



and promoting best practices in close collaboration with the rest of the engineering organization.

Our mission is to equip product builders and business teams with robust, AI-enabled tools and practices to deliver and interpret insights with quality, confidence, and efficiency. We work across teams to improve analytical software patterns, optimize high-scale data queries, and raise the overall data and engineering bar across the company.

Within this context, real-time analytics and intelligent data access are an increasingly important area of focus. As Factorial continues to scale, we want to strengthen how we handle massive-scale data ingestion, build highly efficient OLAP structures, and apply modern LLM workflows to bridge the gap between complex databases and natural language querying.

The role

As an Engineer at Factorial, you’ll be part of a team of 200+ Engineers. We look for people who are curious, proactive, technically stron

📌 Staff AI Analytics Engineer (Barcelona)
🏢 Factorial
📍 Barcelona