Controllers Engineering

Controllers Engineering is responsible for designing and implementing solutions that support financial measurement and reporting, including revenue, balance sheet, liquidity and capital. We also help meet the firm’s global regulatory financial reporting obligations and build tools that drive efficiency and consistency across controller functions.

Responsibilities

• Manage end-to-end systems development in an Agile environment, from requirements analysis through coding, testing, UAT, implementation and maintenance.
• Produce technical designs, testing strategies and implementation plans.
• Partner with Finance stakeholders to understand business needs and translate them into process workflows, data requirements and specifications.
• Build reusable solutions and identify opportunities for cross-divisional collaboration.
• Contribute to data modelling and curation.

Basic Qualifications

• Bachelor’s degree or relevant experience in Computer Science, Mathematics, Electrical Engineering or related discipline.
• 6+ years of software development experience.
• Strong analysis and design skills, plus knowledge of data structures, algorithms and performance-oriented design.
• Strong communication skills with both technical and business audiences, and comfortable working with multiple global stakeholders.

Expert Knowledge in One Or More Of

• Hands-on programming experience in Java or Python
• Significant solutions architecture and system design experience
• Experience of using Agentic AI coding tools - e.g. Claude Code, Co-Pilot Agent Mode, Devin
• Experienced with Cloud Technologies – ideally AWS – e.g. S3, SQS, Lambda, Fargate
• Strong RDBMS knowledge
• Experience developing distributed, micro services-based applications.
• Experience with data modelling and curation for large-scale datasets

Preferred Qualifications

• Knowledge or interest in investment banking or financial instruments
• Experience with big data concepts, such as Lakehouse, ETL data pipelines (e.g. Spark, AWS Glue)
• Experience with near real time and event-based systems like Kafka