Databricks AI Data Enablement Engineer

Xenon Seven; España; On-site; EUR 70,000 - 110,000; Full time

Job summary

Xenon Seven seeks a Data Enablement Engineer to design, build, and operate trusted datasets, semantic models, and embedded AI experiences on our data platform. This role focuses on data foundation engineering, not model training.

You will work on semantic layers, governed data products, and AI-ready pipelines, collaborating with Finance to translate domain needs into reliable data products for business users.

Qualifications

• 5+ years hands-on data engineering on cloud data platforms — Databricks demonstrated in real project delivery, not skill-list-only
• Direct hands-on experience with Databricks Genie — built, configured, and tuned in production or advanced pilots, with Genie flavors
• Semantic layer / trusted data product delivery — governed datasets with KPI definitions, hierarchies, and business glossary alignment
• dbt, PySpark, SQL, Python — strong across the modern data stack
• Orchestration with Airflow, Databricks Workflows, or equivalent
• Data governance in regulated environments — RBAC, RLS, masking, lineage, auditability
• Experience integrating structured and unstructured data into AI-enablement workflows

Responsibilities

• Design and build AI-ready data products on Databricks — trusted datasets with well-defined business semantics, KPIs, hierarchies, and business glossary alignment
• Implement semantic layers and governed datasets that support both traditional BI consumption and natural-language querying by business users
• Deploy and operate Databricks Genie spaces with Unity Catalog, tuning them for accuracy, adoption, and business relevance
• Build RAG pipelines and conversational analytics applications grounded in governed enterprise data — including Streamlit or Databricks Apps that let business users query data without writing SQL
• Engineer robust ETL/ELT pipelines (dbt, Airflow, PySpark) that produce and maintain the trusted data these AI experiences depend on
• Implement data governance — RBAC, row/column-level security, masking, lineage, auditability, catalog and metadata management — in a regulated pharma environment
• Optimize cost and performance on both the data platform side (warehouse sizing, cluster tuning, query optimization) and the AI side (token usage, caching, model routing)
• Partner with Finance business stakeholders to translate domain requirements into semantic models and governed data products they can trust

Skills

Databricks

Genie

Semantic layer

dbt

PySpark

SQL

Python

Airflow

Databricks Workflows

RBAC

RLS

Job description

Xenon Seven seeks a Data Enablement Engineer to design, build, and operate trusted datasets, semantic models, and embedded AI experiences on our data platform. This role focuses on data foundation engineering, not model training.

You will work on semantic layers, governed data products, and AI-ready pipelines, collaborating with Finance to translate domain needs into reliable data products for business users.