Data Engineer (Databricks, Python, Spark) - barcelona
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Description
In this Data Engineer role within Investment Management, you will design and maintain a cloud-based data hub and pipelines that enable large-scale analytics for investment teams. You’ll work with a global, collaborative group and continuously learn to apply the latest data engineering and AI concepts. Your contributions will unlock value from financial data sources like Bloomberg and support cross-functional investment stakeholders. This is a hands-on, growth-oriented opportunity to shape a key platform in a tech-driven environment.
Compensaciones / Beneficios- flexible working model
- home office setup allowance
- training (languages)
- health insurance
- life and accident insurance
- stock options
- Design, develop, enhance, and maintain complex data pipelines for business-critical operations and analytics
- Support internal Investment Management clients and address their needs
- Improve platform capabilities and influence technology choices and standards
- Stay current with evolving data engineering and AI technologies and share knowledge with the team
- Collaborate with experts across domains to deliver real-world data solutions
- Contribute to a culture of continuous learning and creative input
- 3+ years of Data Engineering experience with 2+ years designing and building Databricks data pipelines
- Azure cloud experience preferred (AWS/GCP also considered)
- 2+ years Python/PySpark/SparkSQL and/or Scala
- 2+ years Big Data pipelines or DAG tools (Data Factory, Airflow, dbt)
- 2+ years Spark experience (Databricks Spark and Delta Lake)
- 2+ years implementing Big Data solutions in a cloud ecosystem (Data/Delta Lakes)
- 2+ years SQL with complex queries
- Experience with GitHub and CI/CD pipelines (desirable)
- Experience with financial data providers such as Bloomberg (desirable)
- Experience with AI/LLMs, Databricks Genie or similar tools
- Proficiency in English
- Positive attitude and can-do mentality
- positive attitude
- can-do mentality
- collaboration
- Databricks
- Python
- PySpark
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