Digital Transformation Manager

Function: Digital Transformation Office Reports to: Director Digital Futures Shape the future of digital at HBKHBK is establishing a new Digital Transformation Office (DTO) to accelerate its transformation as a global leader in precision measurement, sensing and industrial technology.The role is explicitly AI-first: leveraging data, AI, and platform thinking as default design principles rather than optional add-ons.The Digital Transformation Manager is a senior, business-facing leader responsible for shaping, prioritising and delivering digitally enabled strategic initiatives across HBK. The role works at the intersection of business strategy, technology, and execution, partnering with Product, R&D, Manufacturing, Operations, Commercial and Corporate functions to:Identify high-value digital opportunitiesTranslate ideas into well-defined initiatives and programmesOversee delivery to measurable outcomesEstablish and operate portfolio governance and PMO disciplinesKey Responsibilities:1. Digital Strategy & IdeationPartner with senior business leaders to identify, frame and shape digital transformation opportunities aligned to HBK’s strategy.Facilitate ideation workshops using AI-first, data-first and platform-led approaches.Challenge problem statements to ensure focus on business value, scalability and reuse, not point solutions.Translate strategic themes into discrete initiatives with clear hypotheses, value drivers and success measures.2. Initiative Definition & Business Case DevelopmentLead end-to-end initiative definition including:Problem statement and outcome definitionTarget-state processes and operating modelsData, AI, platform, cyber and integration implicationsHigh-level architecture and delivery approachDevelop robust business cases including value sizing (financial and non-financial), risks, dependencies and change impacts.Ensure alignment with HBK standards for architecture, security, compliance, and IP protection.3. Portfolio Management & PMO LeadershipCo-define and continuously evolve the Digital Transformation PMO methodology, covering:Portfolio intake and prioritisationFunding and capacity allocationStage gates and decision forumsBenefits tracking and value realisationOperate portfolio-level oversight across initiatives, ensuring:Strategic alignmentDelivery predictabilityDependency and risk managementProvide clear, executive-level portfolio reporting, including RAG status, value delivery, risks and decision requests.4. Execution Oversight & Delivery GovernanceAct as business owner or sponsor delegate for key initiatives.Work with delivery teams (internal and partners) across:AI & dataPlatform and cloud engineeringOT/IT convergenceCybersecurityEnsure delivery teams apply modern delivery practices (Agile/Hybrid) while operating effectively in engineering and manufacturing contexts.Actively remove blockers, manage escalations, and course-correct delivery where needed.5. AI, Data & Platform EnablementEmbed AI as a core design principle, focusing on:Decision automationInsight generationEngineering productivityCustomer value creationPartner with AI, Data, Platform and Cyber Centres of Excellence to:Reuse shared capabilitiesAvoid duplicationAccelerate time-to-valuePromote responsible AI practices, data governance, and security-by-design.6. Change & Stakeholder LeadershipDrive strong engagement across business, engineering and technology communities.Support adoption through change, communication and capability uplift.Act as a visible role model for digital ways of working and outcome-led delivery.Success MeasuresSuccess in this role will be measured by:Realised business value from digital initiativesQuality and robustness of initiative pipeline and portfolioPredictability and transparency of deliveryExecutive confidence in digital investment decisionsEffective reuse of AI, data and platform capabilitiesRequired Skills & CompetenciesCore CapabilitiesDigital strategy execution in complex, engineering-led organisationsStrong AI literacy – able to identify and apply AI use cases (not necessarily hands-on model building)Portfolio and programme management at scaleBusiness case development and value realisationExecutive stakeholder management and facilitationTechnical & Domain UnderstandingWorking knowledge of:Data platforms and analyticsAI/ML applications in industrial, engineering or manufacturing contextsCloud and platform architecturesCybersecurity and compliance considerationsExperience operating across IT, OT, software, hardware and product environments is highly valued.Delivery & Ways of WorkingStrong grounding in Agile, hybrid and scaled delivery models (e.g., SAFe, Spotify-inspired, or custom enterprise models).Comfortable balancing:Speed vs safetyExperimentation vs standardisationGlobal vs local needsExperience working with external partners and system integrators.Leadership & BehavioursOutcome-oriented, pragmatic and commercially mindedConfident influencing without formal authorityComfortable with