Full Stack Engineer (Investment Platform)

This role is known as ‘Investment Platform Engineer’ internally

About the role: The Investment Platforms team bridges the gap between Investments and Technology, partnering closely with the Investment Directorate and Investment Operations teams to deliver technology change and operate platform systems that underpin our Investment Proposition. They manage a diverse and specialist technology landscape, including discrete applications, platform technologies, underlying data stores, market data solutions, and 3rd party managed services. The team works with the broader technology community to ensure Investment systems are scalable, secure, and aligned with business priorities, enabling innovation and operational excellence across the investment lifecycle. As an Investment Platform Engineer, you will engineer and support the end-to-end development, enhancement, and release of platform features using a broad range of technologies including but not limited to; Python, web frameworks, SQL, and React. You will ensure the reliability of internal applications, contribute to the availability and monitoring of automated workloads, and help deliver robust data and application services for investment teams. You will also configure and execute jobs across third-party investment platforms including Bloomberg, Aladdin, and FactSet, acting as a technology SME and partnering with Data, Technology, and Vendor Management teams to ensure enhancements to the investment technology estate are resilient, scalable, and fit for purpose. This is an excellent opportunity for a technical professional looking to specialise in investment management technology, combining software engineering, data engineering, and applied investment systems knowledge. What you’ll be doing: Building, enhancing, and maintaining internal applications to support Investment workflows, using SQL, Python, modern web frameworks and JavaScript/React. Delivering features end-to-end, including development, testing, release, and maintenance. Implementing high-quality engineering practices including code versioning, peer reviews, optimisation, and adherence to development standards. Monitoring and managing automated job execution across internal and third-party systems, escalating and resolving issues where needed. Maintaining highly reliable platform environments, ensuring data stores, APIs, and analytics tools remain available and accurate. Executing and configuring scripted or scheduled processes supporting investment teams. Performing data extraction, manipulation, and analysis using Python and SQL to support application logic and operational workflows. Investigating data anomalies and ensure the accuracy and integrity of investment datasets (security, positions, prices etc). Reconciling systems to ensure consistent data across the platform ecosystem. Acting as an Investment Tech SME when working with Data, Technology, and Vendor Management teams on platform enhancements. Supporting colleagues across Investment functions to self-serve analysis and reporting via platform applications. Contributing to Data Stewardship activities by representing investment data requirements and ensuring upstream changes remain robust. Identifying opportunities to enhance platform workflows, engineering processes, automation, and overall system reliability. Promoting best practices for EUDA (End User Developed Application) governance and coding standards within Investment teams About you: We’re looking for a curious and hands-on engineer with strong Python and SQL skills, a passion for building reliable applications, and the ability to bridge technology and investment teams. You'll be a proactive problem-solver who enjoys improving systems, automating processes, and delivering real business value. Essential Criteria Experienced in building maintaining applications to support internal business processes and workflows. Proficiency in front end app development (React/JavaScript or similar) and web framework (Flask/Django/FastAPI) Highly capable in data pipelining using tools like Airflow DBT, and data extraction, manipulation and reporting using Python SQL. Experience with code versioning, optimisation and associated best practices, including Git, pull requests, unit testing, CI/CD and familiarity with enterprise SDLC Data analysis to investigate and quality control datasets feeding applications. Ideally within an asset management context Desirable Criteria Practical experience building, deploying, or running data/software solutions on cloud infrastructure (AWS/Azure) Experience in using and supporting investment technology platforms such as Bloomberg, Factset, Aladdin, Axioma, Knowledge of typical financial/asset management data domains (positions, security, prices) and common asset classes Special

Requirements: Some business travel may be necessary