SSR Data Engineer

About the project

You will join a Market Risk environment within a large financial organization working on the definition automation and evolution of Big Data processes. The project focuses on data-intensive pipelines used for risk calculation and analytics leveraging distributed technologies and strong data quality standards. You will be part of a Big Data team handling shared platforms and common data challenges across the area.

What you will do

• Design develop and automate Big Data processes using Spark and Scala.
• Build and maintain ETL pipelines and data models for Market Risk use cases.
• Perform data testing validation and quality controls to ensure reliable outputs.
• Work closely with other Big Data engineers on shared frameworks and common tasks.
• Collaborate with risk and technical teams in an international environment.
• Contribute to continuous improvement of Big Data workflows and standards.

Qualifications :

Required:

• 35 years of experience in technology projects involving Big Data or data engineering.
• Hands-on experience designing ETL processes and data models.
• Strong experience with Spark and Scala.
• Solid knowledge of Hadoop ecosystems.
• Advanced SQL skills.
• Experience in data testing and validation.
• Basic Shell scripting knowledge.
• English level B2/C1 (working proficiency).

Nice to have:

• Experience with Azure Databricks.
• Background in banking specifically Market Risk.
• Knowledge of Airflow or similar workflow/pipeline managers.

Additional Information :

What do we offer you

• Hybrid position based in Málaga Spain
• Perks and Benfits such as private medical insurance life insurance language lesson flexible remunerationSmart Office Pack so that you can work comfortably from home
• Permanent full-time contract.
• Training and career development.
• Possibility to be part of a multicultural team and work on international projects.

If you are passionate about data development & tech we want to meet you !

Remote Work :

No

Employment Type :

Full-time