AI Data Enablement Engineer: Semantic Data Platforms

Xenon7; Cerdanyola del Vallés; Presencial; EUR 70.000 - 95.000; Jornada completa

Descripción de la vacante

Xenon7 is hiring a Data Enablement Engineer to design, build, and operate the trusted datasets, semantic models, and embedded AI experiences that let Finance users interact with governed data in natural language.

This data platform engineering role focuses on the data foundation—semantic layers, governed data products, and embedded natural-language analytics—not on training models, ensuring reliability and scalable AI across the enterprise.

Formación

• 5+ years hands-on data engineering on cloud data platforms
• Direct hands-on experience with Databricks Genie
• Semantic layer / trusted data product delivery
• Experience with dbt, PySpark, Snowpark, SQL, Python
• Orchestration with Airflow or Databricks Workflows
• Data governance in regulated environments
• Experience integrating structured and unstructured data into AI-enablement workflows

Responsabilidades

• Design and build AI-ready data products on Databricks
• Implement semantic layers and governed datasets
• Deploy and operate Databricks Genie spaces with Unity Catalog
• Build RAG pipelines and conversational analytics applications
• Engineer ETL/ELT pipelines (dbt, Airflow, Snowpark, PySpark)
• Implement data governance with RBAC, masking, lineage, auditability
• Optimize cost and performance on data platform and AI side
• Partner with Finance stakeholders to translate requirements into semantic models

Conocimientos

Data engineering

Databricks Genie

Semantic modeling

SQL

Python

Airflow

Data governance

Herramientas

Databricks

dbt

PySpark

Snowpark

Streamlit

Power BI

Descripción del empleo

Xenon7 is hiring a Data Enablement Engineer to design, build, and operate the trusted datasets, semantic models, and embedded AI experiences that let Finance users interact with governed data in natural language.

This data platform engineering role focuses on the data foundation—semantic layers, governed data products, and embedded natural-language analytics—not on training models, ensuring reliability and scalable AI across the enterprise.