Data Engineer

Overview 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

Responsabilidades

• 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

Requisitos principales

• - 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/Py
• Spark/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
• Py
• Spark