Data Engineer

A European financial institution known for its work in investment and private banking is expanding its data team. They’re looking for someone who enjoys building reliable data systems, working with cloud technologies, and supporting real-time analytics in a regulated environment.

Responsibilities:

• Build and maintain real-time data pipelines, backend services, and workflow automations.
• Define data models, requirements, and transformation logic across structured and unstructured data.
• Write secure, well-tested code (Python, Scala, or similar).
• Strengthen data governance, quality, and security through scalable data processes.
• Work with Azure, Databricks, Delta/Live Tables, and distributed computing frameworks.
• Troubleshoot issues across pipelines, storage layers, and downstream systems.

Requirements:

• Degree in Computer Science, Data Engineering, Information Systems, or equivalent experience.
• 5+ years building end-to-end data systems, ETL/ELT pipelines, and workflow tools (Airflow, Databricks, etc.).
• Strong SQL skills for diagnosing and validating complex transformations.
• Hands-on experience with large-scale processing (PySpark, Spark Streaming, Delta Tables).
• Experience working in Azure environments, including Data Lake and CI/CD setups.
• Familiarity with Kubernetes, Docker, and event-driven systems (Kafka, Event Hub, Event Grid, Flink).
• Background in Python, Scala, JavaScript, Java, or C#.
• Bonus: knowledge of dbt, Data Vault, or Microsoft Fabric.
• Banking or financial services experience is highly preferred

This is an initial 12-month contract (convertible to permanent) based in Singapore.