Data Platform Engineer, Aberdeen

• The role is for an Engineer with practical experience spanning 2+ years, joining the Development Chapter within the Asset Management Tribe
• We are looking for a highly capable and detail-oriented engineer who thrives on working with complex, high-volume data systems
• You should have a track record of building and maintaining data platforms that are not only robust and scalable, but also efficient and cost-effective
• Your ability to understand and optimise data flows—especially those that are critical to daily and intraday investment operations—will be key to your success in this role
• You will be someone who takes pride in writing clean, performant code and designing modern data solutions that stand up to the demands of a fast-paced, data-driven environment
• You should be comfortable navigating large datasets, applying best practices in data modelling and transformation, and leveraging cloud-native tools to deliver solutions that are both technically sound and operationally sustainable
• A mindset focused on automation, observability, and continuous improvement is essential, as is the ability to collaborate effectively with both technical and non-technical stakeholders
• Experience in Asset Management or Finance Technology
• Experience in SQL
• Solid understanding of ETL development, data modelling, and data governance
• Familiarity with DevOps tooling and CI/CD pipelines
• Strong foundation in software development practices, including unit testing
• Experience with code deployment and production support

Desirable

• Reporting to the Chapter Lead, you’ll work in a cross-functional team to design, develop, and support systems critical to investment operations and reporting
• The focus is on building and maintaining data platforms and pipelines that power investment data products used across the organization for portfolio management, analytics, and regulatory reporting
• Key responsibilities include developing robust, scalable solutions, ensuring data quality and performance, integrating with cloud-native platforms, and contributing to data architecture. Strong skills in data modelling, transformation, governance, and collaboration in an Agile environment are essential
• Design, develop, and maintain robust, scalable data pipelines and services that support investment data products and reporting platforms
• Build and optimise data integration workflows using tools such as Azure Data Factory, Synapse Pipelines, and SQL/T-SQL, ensuring data quality, performance, and reliability
• Contribute to the evolution of our cloud-native data architecture, leveraging Azure Databricks, Azure Data Lake, and Snowflake where appropriate
• Apply strong data modelling and transformation skills to support analytics, regulatory reporting, and operational use cases
• Promote and implement engineering best practices, including test automation, unit testing, and CI/CD pipelines
• Ensure observability and operational readiness of data solutions, including logging, monitoring, and Level 3 production support
• Support data governance and metadata management initiatives to ensure data integrity and compliance
• Explore and apply AI-assisted development tools (e.g. GitHub Copilot) and automation to improve engineering efficiency and solution quality
• Participate in Agile ceremonies and contribute to continuous delivery and iterative improvement of our data platforms
• Participate in code reviews, pair programming, and knowledge sharing
• Drive continuous improvement in development tools, processes, and team ways of working

• End Date: December 20, 2025