SENIOR Databricks Engineer

RiskPod; Comunidad de Madrid; Presencial; EUR 63.837 - 83.763; Jornada completa

Descripción de la vacante

RiskPod is seeking a Databricks Data Engineer for a 12-month contract based in Comunidad de Madrid, Spain. The ideal candidate will have 6-10 years of experience and must be proficient in Databricks and PySpark.

In this role, you will design and develop comprehensive data pipelines, ensuring high performance and maintainability. Strong analytical skills and the ability to work independently on data ingestion and transformation tasks are essential.

Formación

• 6-10 years of experience in data engineering.
• Strong hands-on experience with Databricks and PySpark.
• Ability to implement data pipelines independently.

Responsabilidades

• Design and develop data pipelines from source systems.
• Implement data ingestion and transformation using Databricks.
• Build scalable data processing pipelines in PySpark.
• Maintain data quality and performance.

Conocimientos

Databricks expertise

Advanced PySpark development

End-to-end data pipeline development

Data ingestion from multiple sources

Strong SQL skills

Descripción del empleo

My client is looking for a Databricks Data Engineer - 12 Month Contract paying 400 Euros per day.

Work Timings: Swiss/Spanish Business Hours

Experience Range: 6-10 years

Mandatory Skills

• Strong hands-on experience in Databricks
• Advanced PySpark development
• Experience building end-to-end data pipelines
• Expertise in data ingestion from multiple sources (APIs, databases, files, etc.)
• Strong SQL and data transformation skills

Key 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 maintainability

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