Data Engineer

Job Overview

Our client, a leading global financial institution, is seeking a Data Engineer to join their data and analytics team. This role is ideal for a technically strong engineer who enjoys building scalable data platforms and production-grade machine learning systems that support commodity management and business decision-making at scale.

• Design, build, and maintain scalable, production-ready data pipelines on Azure and Databricks to support machine learning and analytics use cases.
• Develop, deploy, and operationalize machine learning models (regression, classification, NLP, and time series forecasting) with a focus on robustness, performance, and maintainability.
• Translate business and quantitative requirements into reliable, reusable data and ML solutions.
• Collect, process, and manage large volumes of structured and unstructured data from internal and external sources.
• Implement MLOps best practices, including model versioning, CI/CD, monitoring, retraining workflows, and performance tracking.
• Optimize data workflows for accuracy, timeliness, scalability, and cost efficiency.
• Collaborate with data scientists, data engineers, and platform teams to ensure consistent architecture and coding standards.
• Monitor production pipelines and models, troubleshoot issues, and continuously improve system reliability and performance.
• Contribute to the definition of best practices and standards for data engineering, machine learning deployment, and cloud-based solutions.

The preferred candidate should possess experience working with Python code and strong knowledge of Dev Ops practices (e.g., Git, Agile methodology), Azure, and Databricks. Excellent communication and interpersonal skills are expected, with the ability to interact at all levels of business efficiently.

If you are interested in this opportunity, please email your C.V. to contact or call Altus Search on  21 for a confidential discussion.

Mid-Senior level

Full-time

Finance and Information Technology

Zurich, Switzerland

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