> Markdown version of [/jobs/ext/3977161-databricks-engineer-400-a-day](https://www.wearedevelopers.com/jobs/ext/3977161-databricks-engineer-400-a-day). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Databricks Engineer - €400 A Day

- **Company:** Riskpod
- **Location:** Zaragoza, Spain
- **Salary:** €104,000
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Big Data, Databases, Data Transformation, Python (Programming Language), Performance Tuning, Standard Sql, Data Processing, Data Ingestion, Pyspark, Data Pipelines, Databricks
- **Published:** October 28, 2026
- **Apply:** https://www.buscojobs.com.es/databricks-engineer-%E2%82%AC-400-a-day-en-zaragoza-ID-378011630

## About the Role

for strong hands-on engineers who can write PySpark/Python code and implement pipelines independently.

## Description

My client is looking for a Databricks Data Engineer - 12 Month Contract paying 400 Euros per day.Role: Databricks Data EngineerWork Timings: Swiss/Spanish Business HoursExperience Range: 6-10 yearsLocation: Spain/ Madrid / Near locationMandatory Skills:· Strong hands-on experience in Databricks· Advanced PySpark development· Strong Python programming· Experience building end-to-end data pipelines· Expertise in data ingestion from multiple sources (APIs, databases, files, etc.)· Experience implementing Medallion architecture (Bronze ? Silver ? Gold layers)· Strong SQL and data transformation skills· Experience handling large-scale data processingKey Responsibilities:· Design and develop data pipelines from source systems to Gold layer datasets· Implement data ingestion, transformation, and optimization using Databricks· Build scalable PySpark-based data processing pipelines· Ensure data quality, performance optimization, and maintainabilityImportant Note:Client is specifically looking for strong hands-on engineers who can write PySpark/Python code and implement pipelines independently.