Overview
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In this StaffAI Analytics Engineer role, you will help shape Factorial’s analytics platform with a strong emphasis on advanced analytical architectures, semantic modeling, and AI/LLM-powered data workflows. You’ll work within the DX and Performance team to improve real-time analytics, data access, and scalable pipelines that empower product and business teams. This position offers the chance to influence architectural decisions and drive AI-enabled analytics across the company. You’ll join a mission to deliver robust, high-quality insights at scale.
Compensaciones / Incentivos
Alan private health insurance
Wellhub (fitness benefits)
Cobee expense management
Language classes
Breakfast in the office and organic fruit
Pet Friendly
Responsabilidades
Lead evolution of Factorials analytics platform and how data becomes actionable for millions of users
Design high-performance pipelines using ClickHouse and Kafka-based streaming
Define and architect semantic models/cubes (measures, dimensions, joins, pre-aggregations)
Integrate LLMs into analytics workflows (text-to-SQL, natural-language querying, conversational BI) with governance
Apply prompt engineering, tool calling,



and embedding-based retrieval (RAG)
Build shared capabilities to enable other teams to develop intelligent analytic experiences
Lead architectural decisions around modeling, performance, governance, observability, and scalability
Collaborate with Product, Engineering, Analytics, and Data Science to translate business questions into scalable solutions
Requisitos principales
Strong SQL skills with hands-on ClickHouse experience (queries, materialized views, MergeTree)
Solid OLAP fundamentals (dimensional modeling, aggregations, star/snowflake schemas)
Experience defining/building semantic layers/cubes (e.g. Cube. xqbhyrx js)
Experience integrating LLMs into structured analytics (RAG, text-to-SQL, tool calling)
Proficiency in TypeScript for tooling, APIs, and data integrations
Willingness to work with Ruby on Rails backends (optional)
Familiarity with cloud environments (AWS/GCP), Docker, Kubernetes
Experience with BI and data transformation tools (Cube.js, dbt, LookML, Superset)
Curiosity and proactive problem-solving
Effective communication across cross-functional teams
Strong collaboration with Product, Engineering, Analytics, and Data Science
ClickHouse (OLAP store)
Kafka (streaming ingestion)
TypeScript

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