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# Staff AI Analytics Engineer

- **Company:** Factorial
- **Location:** Spain
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Data Analysis, Automated Storage and Retrieval Systems, Encodings, Data Governance, Database Queries, Dimensional Modeling, Online Analytical Processing, Query Optimization, SQL Databases, Systems Integration, TypeScript, Large Language Models, Prompt Engineering, Data Layers, Data Analytics, Apache Kafka, Vertica
- **Published:** July 10, 2026
- **Apply:** https://es.trabajo.org/oferta-5354-af9854754f7fb540992796a0e99aba6a

## About the Role

equivalent columnar OLAP stores) query optimization, materialized views, and MergeTree engines - Solid grasp of OLAP fundamentals: dimensional modeling, aggregations, and star/snowflake schemas - Proven experience building or defining semantic layers / cubes (e.g. Cube.js) - Experience integrating LLMs into structured data analytics. RAG, text-to-SQL, or tool/function calling - Proficiency in TypeScript for building tools, APIs, and data layer integrations Preferred Experience - Experience working with Ruby on Rails backends (or strong willingness to work within one) - Familiarity with vector databases and embedding-based retrieval systems -

## Description

high-performance analytical pipelines using ClickHouse and streaming ingestion with Kafka - Develop and architect custom semantic models and cubes from scratch, defining measures, dimensions, joins, and pre-aggregations - Integrate LLMs into analytics workflows: text-to-SQL, natural-language querying, and conversational BI, ensuring accuracy and governance over results - Apply advanced prompt engineering, tool/function calling, and embedding-based retrieval (RAG over structured data) - Build shared capabilities that will serve as the foundation for other teams to develop intelligent analytical experiences across the platform - Lead architectural decisions around analytical modeling, performance, data governance, observability, and scalability - Collaborate closely with Product, Engineering, Analytics, and Data Science teams to turn complex business questions into scalable, reusable solutions Qualifications & Experience - Strong SQL skills and hands-on experience with ClickHouse (or


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