10+ years of industry experience with significant C-level executive exposure and proven track record managing large enterprise accounts
Proven success in financial services is highly regarded, with the ability to balance the needs of the centralised architecture and engineering divisions with those of the organizational business units (Retail, Business, Institutional, Wealth, Risk)
Experience working with modern data technology (e.g. dbt, spark, containers, devops tooling, orchestration tools, git, etc.)
Deep expertise in cloud data platforms, AI/ML technologies (including LLMs, machine learning pipelines, and MLOps), data warehousing, and modern data architecture
Hands-on expertise with SQL, Python, and data modeling concepts, with ability to explain complex technical architectures in business terms
Exceptional presentation and communication skills specifically with C-level executives, including demonstrated ability to translate highly complex technical concepts into compelling business value propositions that drive executive decision-making
Proven experience working with product management teams to influence roadmaps, prioritize features, and drive customer-centric development through effective internal advocacy
Outstanding ability to conduct executive briefings, board presentations, and strategic planning sessions with senior leadership teams across technical and business functions
Strong track record of internal advocacy within technology companies, representing customer needs to product and engineering organizations while facilitating cross-functional collaboration
University degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred. Masters in Data Science or Business Administration is a plus
Experience facilitating C-level strategic planning sessions focused on data and AI strategy would be beneficial but not required