Data Engineer - AI Transformation Programme

About the role

Lombard Odier Investment Managers is looking for a Data Engineer to join its Data Management Team and contribute to a large-scale data and AI transformation programme. You will build and maintain robust, scalable and trusted data pipelines that feed investment processes, business development, operations and AI solutions, working in cross-functional squads with AI Engineers, AI Transformation Managers and business stakeholders.

Key responsibilities

• Build and maintain data pipelines that turn raw data from internal systems and vendors into trusted datasets for business, analytics and AI use cases.
• Support ingestion and processing of structured and unstructured data such as investment data, research content, client communications, regulatory documentation and operational datasets.
• Ensure data freshness, consistency, reliability and accessibility across critical pipelines.
• Contribute to modern data architectures, reusable data products and datasets.
• Implement data quality controls, monitoring and observability across production pipelines.
• Support data governance: metadata management, data cataloguing, lineage, traceability and documentation, and help set data standards and best practices.
• Document data flows, transformations and dependencies and support continuous improvement of the data platform.
• Work with AI Engineers, data platform teams and business stakeholders to turn data requirements into scalable solutions, and partner with data owners and domain experts.

Required profile

• Master's degree in Computer Science, Data Engineering or a related field.
• 3-5 years of experience in Data Engineering or a similar role.
• Hands-on experience with modern data platforms such as Snowflake, Microsoft Fabric or equivalent.
• Experience building and maintaining production-grade data pipelines, and with both structured and unstructured data.
• Strong understanding of data quality principles and monitoring in production environments.
• Interest in modern AI technologies and data architectures; exposure to financial services is a plus.
• Team player with strong communication skills, autonomous and pragmatic.

Required skills

• Very strong Python and SQL skills.
• Data modelling, ETL/ELT processes and data integration patterns.