Location: Madrid, Spain – Hybrid
Work Hours: Swiss/Spanish business hours
Experience: 6–10+ years
Engagement: Contract ( 6 months with extensions)
Start: Immediate / ASAP
The Opportunity
We are looking for a highly hands‑on Senior Databricks Data Engineer to design, build, and optimize scalable end‑to‑end data pipelines.
This role is best suited to an engineer who is comfortable writing PySpark/Python code independently, working with large datasets, integrating multiple data sources, and taking data from initial ingestion through Bronze, Silver, and Gold layers using Medallion Architecture.
This is not a coordination‑only or architecture‑only position. We are specifically seeking someone who remains hands‑on with Databricks, Spark, PySpark, Python and SQL.
Key Responsibilities
Design, develop, and maintain scalable Databricks‑based data pipelines.
Build end‑to‑end data engineering solutions from source ingestion through Gold‑layer datasets.
Develop high‑performance data processing workflows using PySpark, Python, Spark and SQL.
Integrate data from multiple sources,



including APIs, databases, files, cloud storage and external platforms.
Design and optimize Databricks architectures for data ingestion, transformation, processing and storage.
Work with large‑scale datasets and distributed data processing environments.
Perform Spark/Databricks performance tuning to improve processing speed, scalability and cost efficiency.
Build robust ETL/ELT workflows with appropriate data quality, monitoring and governance controls.
Optimize Databricks workflows, jobs and compute resources.
Troubleshoot pipeline performance, reliability and data‑quality issues.
Collaborate with Data Architects, Data Engineers and business stakeholders to translate requirements into production‑ready data solutions.
Contribute to engineering standards and Databricks best practices.
Mandatory Technical Skills
you demonstrate strong production‑level experience with:
Databricks
Python
Advanced SQL
Medallio

📌 Databricks Data Engineer (Madrid)
🏢 Talent To Hire
📍 Madrid