Data Manager

Who We Are VML is a global creative company that combines brand experience, customer experience, and commerce to create connected brands that drive growth. Guided by a Human First philosophy, VML is known for its innovative work for brands and consistently ranks among the world’s leading creative companies, including the WARC Creative 100. VML’s global network spans 55+ markets with principal offices in Buenos Aires, Kansas City, London, New York, São Paulo, Shanghai and Singapore. VML is part of WPP, the trusted growth partner for the world's leading brands. Powered by exceptional talent and our agentic marketing platform WPP Open, WPP unites cutting-edge media intelligence and data solutions, creativity, production, enterprise solutions and expert strategic counsel. For more information, please visit www.vml.com and follow along on   LinkedIn #WeAreVML. VML Luxembourg VML Luxembourg is one of the leading Amazon consulting agencies in Europe. Offering 360° services for Amazon, we have a diverse range of products and services in various sectors to ensure long-term sales growth, ranging from creating multilingual content and listings to all aspects of advertising, including sales promotion, PPC and programmatic campaigns. We are part of WPP, the world’s largest digital media agency, and manage WPP’s European Center of Excellence for Amazon (ACE) dedicated to maximising performance, driving sales and building brands on the Amazon platform. The opportunity: We’re looking for a Data Manager to lead our Data Services team in Luxembourg. This is a senior player-manager role at the intersection of technical leadership, commercial delivery, and client engagement. You’ll lead a cross-functional team of Data Scientists, Senior BI Engineers, and Data Analysts, and serve as the primary point of contact for internal stakeholders and external clients, from scoping and prioritisation through execution and impact. This is not a purely managerial role. You’ll stay hands-on, building, debugging, and shipping solutions when speed demands it or technical complexity requires your senior judgment. We’re looking for someone who pairs deep technical fundamentals in data, engineering, statistics, and ML with a modern, AI-assisted way of working. You use AI tools to move faster and think bigger, but your instincts and quality bar are rooted in genuine technical mastery, not reliant on it. You can tell when an AI-generated output is wrong, why it’s wrong, and how to fix it. You’ll partner closely with IT to ensure the infrastructure, tooling, and delivery pipelines your team relies on are robust, scalable, and fit for purpose. What you’ll be doing: • Team Leadership & People Management • Lead, mentor, and develop the team, fostering a culture of technical excellence, collaboration, and continuous improvement. • Set clear priorities, allocate workload, and remove blockers so the team can do its best work. • Run regular 1:1s, performance reviews, and career development conversations. • Champion an AI-assisted working culture, encouraging intelligent use of AI tools while holding the bar on rigour, validation, and engineering quality. • Create an environment where team members own their domains and grow toward greater autonomy and seniority. • Agile Delivery & Team Rhythm • Introduce and sustain light Scrum practices sized to the team, lean and purposeful, never bureaucratic. • Own the team’s JIRA workflow: groomed backlog, clear and actionable tickets, transparent tracking from intake to delivery. • Facilitate standups, sprint planning, reviews, and retrospectives, focused, time-boxed, and genuinely useful. • Use sprint cadences to create predictable delivery rhythms and give stakeholders reliable visibility into progress. • Continuously refine team processes based on retrospective learnings, velocity patterns, and stakeholder feedback. • Business & Client Engagement • Act as the primary point of contact for internal stakeholders (Media, Content, Account teams) and external clients on all Data Services requests. • Lead discovery and scoping, translating ambiguous business questions into structured problem statements, delivery plans, and success criteria. • Maintain a prioritised backlog, making transparent trade-offs that balance client urgency, strategic value, and team capacity. • Manage stakeholder expectations across the delivery lifecycle, communicating progress, risks, and outcomes clearly and confidently. • Hands-On Technical Contribution • Stay an active technical contributor, building, reviewing, debugging, and fixing across the team’s stack when needed. • Apply hands-on skills across SQL, Python, dbt, BigQuery, AWS, Power BI, and Looker Studio, shipping production-quality work yourself, not just advising. • Define and enforce technical standards across data modelling, analytics, visualisation, and ML/statistical approaches. • Partner with IT on data infrastructure, system integrations, and the technical enablement needed to deliver reliably at scale. • AI-Assisted Development, Accelerated, Not Undisciplined • Use AI coding and reasoning assistants (GitHub Copilot, Cursor, Claude, ChatGPT) to write, refactor, and review SQL, Python, dbt models, and analytical outputs, as force multipliers on a strong technical foundation. • Leverage automation and orchestration tools (n8n, LangGraph, Make, or similar) to eliminate repetitive work in data processing, reporting, and workflow management. • Apply disciplined practices: clear prompting, thorough code review, systematic testing, rigorous debugging, never shipping AI output without understanding it. • Bring an ML and AI lens to client problems, identifying where predictive models, recommendation logic, NLP, anomaly detection, GenAI, or LLM-based approaches can create real business value, and leading the team to operationalise them responsibly. • Critically evaluate emerging AI/ML tools with pragmatism and a clear eye on quality, explainability, and cl