AI Data Platform Engineer — Semantic Layers & Governed Data

Xenon7; Barcelona; Presencial; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

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

This data platform engineering role focuses on building a robust data foundation, semantic layers, and governance to support AI-enabled analytics, including RBAC, lineage, and cost/performance optimization across Snowflake and Databricks ecosystems.

Formación

• 5+ years hands-on data engineering on cloud data platforms.
• Direct hands-on experience with Snowflake Cortex or Databricks Genie.
• Semantic layer / trusted data product delivery with KPI definitions.
• dbt, PySpark, Snowpark, SQL, Python in modern data stack.
• Orchestration with Airflow or Databricks Workflows.
• Data governance in regulated environments (RBAC, RLS, masking).
• Experience integrating structured and unstructured data into AI workflows.

Responsabilidades

• Design and build AI-ready data products on Snowflake and/or Databricks.
• Implement semantic layers and governed datasets for BI and NL querying.
• Deploy Snowflake Cortex or Databricks Genie configurations in production.
• Build RAG pipelines and conversational analytics apps (Streamlit/Databricks Apps).
• Engineer robust ETL/ELT pipelines (dbt, Airflow, Snowpark, PySpark).
• Implement data governance with cataloging, lineage, and auditability in regulated pharma environments.
• Collaborate with Finance stakeholders to translate domain requirements into semantic models.

Conocimientos

Data engineering

Snowflake

Databricks

dbt

PySpark

SQL

Python

Airflow

RBAC

Herramientas

Snowflake Cortex

Databricks Genie

Snowpark

Descripción del empleo

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

This data platform engineering role focuses on building a robust data foundation, semantic layers, and governance to support AI-enabled analytics, including RBAC, lineage, and cost/performance optimization across Snowflake and Databricks ecosystems.