AI Data Platform Engineer — Trusted Analytics & NLP

Xe7 Limited; España; On-site; EUR 70,000 - 90,000; Full time

Job summary

Xenon7 in Spain is hiring an AI Data Enablement Engineer to design, build and operate trusted datasets with semantic models for enterprise data experiences. This role focuses on data platform engineering, not model training.

You will own the data foundation, implement governed datasets, and enable AI-ready data products for business users across Finance with natural-language analytics.

Qualifications

• 5+ years hands-on data engineering on cloud data platforms.
• Direct hands-on experience with Databricks Genie.
• Semantic layer / trusted data product delivery with KPI definitions.
• dbt, PySpark, SQL, Python — strong across the modern data stack.
• Orchestration with Airflow, Databricks Workflows, or equivalent.
• Data governance in regulated environments — RBAC, masking, lineage, auditability.

Responsibilities

• Design and build AI-ready data products on Databricks with semantic models, KPIs and business glossary alignment.
• Implement semantic layers and governed datasets supporting BI and natural-language querying.
• Deploy and operate Databricks Genie spaces with Unity Catalog for accuracy and adoption.
• Build RAG pipelines and conversational analytics apps grounded in governed data (Streamlit/Databricks Apps).
• Engineer robust ETL/ELT pipelines (dbt, Airflow, PySpark)
• Implement data governance — RBAC, RLS, masking, lineage, auditability, catalog management.
• Optimize cost and performance on data platform and AI sides.
• Partner with Finance stakeholders to translate domain requirements into governed data products.

Skills

Cloud data platforms

Data governance

ETL/ELT design

Semantic modeling

KPI definitions

Tools

Databricks

Databricks Genie

dbt

PySpark

SQL

Python

Airflow

Unity Catalog

Streamlit

Job description

Xenon7 in Spain is hiring an AI Data Enablement Engineer to design, build and operate trusted datasets with semantic models for enterprise data experiences. This role focuses on data platform engineering, not model training.

You will own the data foundation, implement governed datasets, and enable AI-ready data products for business users across Finance with natural-language analytics.