AI Data Enablement Engineer - Databricks Genie

Xenon Seven; Mataró; On-site; EUR 70,000 - 100,000; Full time

Job summary

Xenon Seven is seeking a Data Enablement Engineer in Spain to design, build, and operate trusted datasets and semantic models for AI-enabled analytics. You will work on a data foundation that makes AI reliable, including governance, semantic layers, and embedded NL experiences.

The role focuses on building AI-ready data products on Databricks, deploying Genie spaces, and delivering scalable data pipelines with dbt, PySpark, and Airflow.

Qualifications

• 5+ years hands-on data engineering on cloud data platforms with real project delivery.
• Hands-on experience with Databricks Genie — production or advanced pilots.
• Delivery of semantic layers and governed data products with KPI definitions and glossary alignment.
• Strong SQL, Python, PySpark and modern data stack skills.
• Experience orchestrating with Airflow or Databricks Workflows.
• Knowledge of RBAC, data governance and compliance in regulated environments.

Responsibilities

• Design and build AI-ready data products on Databricks with trusted datasets.
• Implement semantic layers and governed datasets for BI and NL querying.
• Deploy and operate Databricks Genie spaces and Unity Catalog configurations.
• Build RAG pipelines and apps enabling business users to query data without SQL.
• Create robust ETL/ELT pipelines (dbt, PySpark) maintaining trusted data foundations.
• Govern data with RBAC, masking, lineage, and auditability in regulated settings.
• Optimize costs and performance across data platform and AI stacks.
• Collaborate with Finance stakeholders to translate requirements into semantic models.

Skills

Databricks Genie

SQL

Python

PySpark

dbt

Airflow

Data governance

Tools

Databricks

Snowpark

Unity Catalog

Streamlit

Databricks Workflows

Job description

Xenon Seven is seeking a Data Enablement Engineer in Spain to design, build, and operate trusted datasets and semantic models for AI-enabled analytics. You will work on a data foundation that makes AI reliable, including governance, semantic layers, and embedded NL experiences.

The role focuses on building AI-ready data products on Databricks, deploying Genie spaces, and delivering scalable data pipelines with dbt, PySpark, and Airflow.