Job Specifications
At Aberdeen, our ambition is to be the UK's leading Wealth & Investments group.
Strengthening talent and culture is one of our strategic priorities. We strive to make Aberdeen a great place to work so that we can attract and retain the industry's best talent.
Our people put our stakeholders at the heart of everything they do by helping us to make a positive difference to the lives of our clients, customers, colleagues, shareholders, and society.
We are focused on growing our direct and advised wealth platforms and repositioning our specialist asset management business to meet client demand. We are committed to providing excellent client service, supported by leading technology and talent.
Aberdeen comprises three businesses, interactive investor (ii), Investments, and Adviser, each of which focuses on meeting and adapting to our clients' evolving needs:
interactive investor, the UK's second largest direct-to-consumer investment platform, enables individuals in the UK to plan, save, and invest in the way that works for them.
Our Adviser business provides financial planning solutions and technology for UK financial advisers, enabling them to create value for their customers.
Our Investments business is a specialist asset manager that focuses on areas where we have both strength and scale to capitalise on the key themes shaping the market, through either public markets or alternative asset classes.
About the Department
As an Engineer (Data Platforms), you will be a member of the Development Chapter within the Asset Management Tribe, reporting to the Development Chapter Lead and working as part of a cross-functional team. You will contribute to the design, development, and support of systems that are critical to our investment operations and reporting capabilities. The solutions you develop will support investment professionals across the firm, giving you visibility and the chance to make a tangible impact on decision-making and operational efficiency.
About the Role
This role is focused on building and maintaining the data platforms and pipelines that underpin our investment data products. These products are central to many of the initiatives within the Tribe and are used across the organisation to support portfolio management, analytics, and regulatory reporting. As such, we are looking for engineers who can hit the ground running - with the ability to quickly understand investment data, navigate complex data flows, and deliver robust, scalable solutions.
You will work closely with data analysts, investment teams, and other engineers to ensure the quality, availability, and performance of our data products. This includes developing and maintaining data pipelines, integrating with cloud-native platforms, and contributing to the evolution of our data architecture. A strong understanding of data modelling, transformation, and governance is essential, along with the ability to collaborate effectively in a fast-paced, Agile environment.
Key Responsibilities
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.
Support data governance and metadata management initiatives to ensure data integrity and compliance.
Explore and apply AI-assisted development tools (eg GitHub Copilot) and automation to improve engineering efficiency and solution quality.
About the Candidate
We are looking for a highly capable and detail-oriented engineer who thrives on working with complex, high-volume data systems. 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.
The ideal candidate will possess the following:
Understanding of Agile delivery and collaborative development in an Asset Management or Finance Technology environment
Experience in SQL
Exposure to cloud platforms such as Azure and Snowflake
Understanding of Python for data engineering and transformation
Familiarity with DevOps tooling and CI/CD pipelines
Strong foundation in software development practices, including unit testing, code deployment and production