SVP/VP, AdTech Lead, Performance Marketing Platforms, Group Marketing & Communications

DBS · Singapore

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Business Function:

Group Marketing & Communications is responsible for building, protecting, and enhancing the DBS brand in an increasingly commoditised banking industry. Working closely with all units within the DBS Group, we create and execute integrated strategies that focus on communications especially digital communications, marketing, and research to differentiate - and elevate - our brand from the rest of the competition.

Job Purpose

• This is a hands-on product and platform leadership role, not a day-to-day campaign operations position. The successful candidate should have the technical expertise to interpret API documentation, design solutions and requirements, lead prototypes, validate integrations, and approve production solutions with Technology and Data teams.
• Build and scale DBS’s in-house performance marketing platform, controls, and operating Own the AdTech product strategy, roadmap, AdTech architecture, AdOps standards, audience activation, measurement, and transition of selected repeatable media activities from agencies to DBS.
• Create a hybrid operating model that reduces unnecessary agency reliance while preserving access to specialist expertise and flexible capacity.
• Develop an enterprise performance marketing capability across Marketing, Data, and Technology, directly influencing platform strategy, operating standards, investment priorities, and measurable business outcomes across markets.

Key Responsibilities

• Strategy and roadmap: Define the target operating model for in-house paid digital media capability, overall product strategy, target architecture, capability backlog and success measures for performance marketing platforms, AdTech and AdOps.
• Platform ownership: Establish DBS-owned account, access and campaign structures across Google, Meta, LinkedIn, TikTok and approved programmatic platforms, including clear controls for agency and market access. Define automation, machine learning and AI capabilities to enable scalable, agentic media planning, audience targeting, bid optimisation, creative generation, execution and performance optimisation.
• AdTech product delivery: Convert marketing needs into solution designs, API and data requirements, event schemas, acceptance criteria, non-functional requirements and production-readiness standards. Deliver the capabilities working with Technology, Data Engineering, Analytics and platform partners.
• Performance creative enablement: Connect paid-media requirements with in-house creative automation by defining channel specifications, reusable templates, creative metadata, testing frameworks, asset refresh rules and governance for AI-generated content.
• AdOps capability and controls: Define standards for trafficking, naming, permissions, tags, pixels, events, feeds, conversion validation, launch QA, budget controls, brand safety, incidents and change management.
• Audience and signal activation: Lead the roadmap for first-party audience activation, exclusions, audience synchronization, server-side tagging, conversion APIs, enhanced and offline conversions, and media-platform feedback loops.
• Measurement and optimisation: Define the conversion framework and closed-loop measurement capability covering attribution, incrementality, experimentation, automated bidding, value signals and business-outcome reporting. Own the technical requirements for signal quality (tracking, conversions, audience feeds) in partnership with Data Engineering
• Hybrid operating model: Decide which repeatable activities should be operated internally, and which specialist services should remain with agencies. Establish service levels, decision rights, handoffs, scorecards and escalation paths.
• Leadership and governance: Align senior stakeholders across Marketing, Technology, Data, Analytics, Risk, Legal, Procurement, markets, agencies and media platforms. Own investment cases, delivery governance and measurable outcomes.

Requirements

• 12+ years across performance marketing, paid media, AdTech, AdOps or digital platform product leadership, including ownership of enterprise-scale transformation and delivery.
• Deep working knowledge of Google Ads and Google Marketing Platform, Meta Ads Manager, LinkedIn Campaign Manager, TikTok Ads and relevant programmatic platforms.
• Hands-on understanding of Google Ads API, Meta Marketing API, LinkedIn Advertising API and platform authentication, permissions, account hierarchies, campaign, audience, creative, reporting and conversion services.
• Working knowledge of GA4, Google Tag Manager and server-side tagging, AppsFlyer, conversion and event APIs, enhanced and offline conversions, audience matching and customer-data or audience-activation platforms such as Tealium.
• Ability to interpret API documentation, JSON payloads, event schemas, data mappings and integration logs; shape prototypes; diagnose defects; and assess implementation quality and production readiness.
• Practical experience establishing or governing AdOps across account setup, campaign trafficking, access, tagging, audience onboarding, feeds, conversion validation, launch QA and operational support.
• Proven leadership across Marketing, Technology, Data Engineering, Analytics, external platform or agency partners.
• Strong understanding of Data Science, Machine Learning and AI product development, including model lifecycle management, experimentation frameworks, predictive marketing, recommendation systems, generative AI and agentic workflows. Experience defining requirements for AI-enabled marketing capabilities and translating business objectives into scalable data and AI solutions.
• Demonstrated experience designing or materially improving an in-house or hybrid performance-media operating model, including agency transition and capability transfer.
• Experience in financial services or another regulated environment is strongly preferred.
• Strong command of automated bidding, signal quality, campaign architecture, attribution, incrementality, experimentation and closed-loop optimisation.
• Knowledge of access governance, privacy, brand safety, media quality, change and incident controls, including governance for AI-generated advertising assets.
• Product-led and outcome-oriented, with the ability to connect business goals, customer value, platform decisions and measurable results.
• Technically credible without losing commercial judgement or becoming a pure engineering specialist.

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