Director, Data & AI (m/f/d) - Luxembourg

Are you looking to join a world-class manufacturing organization? At Husky TechnologiesTM, we strive to be the best with a strong foundation built on innovation, collaboration and a unique culture with great people. If you are attracted to bold goals, believe in uncompromising honesty, support mutual respect, care about environmental responsibility, have a passion for excellence and a desire to make a positive contribution – we want you to join the Husky TechnologiesTM team! What we offer Excellent benefits package and retirement savings plans as well as life insurance program Competitive vacation policy promoting work-life balance Challenging career opportunities and growth Opportunity to work, innovate and collaborate with passionate people who drive change Amazing team – we are the best in the world at what we do! Husky TechnologiesTM Campus Large, beautiful campus with clean, state-of-the-art air-conditioned offices and manufacturing facilities with high air quality, climate control and outstanding safety records Onsite fitness and wellness center Organized out- and indoor sports activities such as running teams, and bicycle teams Access to onsite medical practitioners Onsite cafeterias with fresh and healthy meal options Free parking Job Description Husky is accelerating its use of AI, analytics and data platforms to improve decision speed, operational efficiency, customer experience and cost transparency. We are seeking a Director of Data & AI who combines hands-on technical depth, product-minded delivery, business partnership and pragmatic governance. The role leads the global Data & AI Office and works in a hub-and-spoke model with business leaders, AI Champions, process owners, architecture, cybersecurity, finance and operations. The Director is accountable for turning data and AI opportunities into measurable business outcomes while ensuring data quality, security, compliance, responsible AI and ITGC-aligned delivery. This is not a pure policy or reporting role. The successful candidate must be comfortable operating close to the technology, challenging complexity, enabling rapid pilots, scaling what works and building the standards required to make AI safe, repeatable and enterprise-ready. Responsibilities Delivery, Product and Business Value Build and run a portfolio of AI, analytics and data products, prioritizing initiatives with clear business value and measurable outcomes. Lead rapid experimentation and scale successful pilots into stable, reusable enterprise capabilities. Partner with business leaders and process owners to identify where AI and trusted data can remove friction, improve decisions or redesign work. Define value cases, adoption metrics and benefit-realization methods for AI and data initiatives. Create reusable delivery patterns for AI agents, analytics products, predictive models, knowledge solutions and automation. Hands-On Technical Leadership Remain close to the technical work: review architectures, data models, integration approaches, AI agent designs, prompt/RAG patterns, ML use cases and platform decisions. Guide teams on modern cloud data platforms, data warehousing, data products, analytics engineering, Python/SQL practices, MLOps and GenAI solution design. Work with architecture, cybersecurity and infrastructure teams to ensure AI/data solutions are secure, scalable and operationally supportable. Challenge over-engineering and promote pragmatic designs that can deliver business value quickly without creating long-term technical debt. Data Strategy, Governance and Quality Develop and execute the enterprise data strategy aligned with business priorities and AI readiness. Establish data ownership, stewardship, quality standards, metadata practices and trusted-data principles across the organization. Improve data quality, lineage, accessibility and consistency across core business domains and platforms. Ensure compliance with applicable data protection, security, privacy, retention and industry requirements. AI Governance and Responsible AI Lead practical AI governance that enables responsible innovation rather than slowing delivery. Define standards for AI use-case intake, risk assessment, knowledge-source validation, model/agent review, access control, monitoring and periodic review. Ensure AI initiatives meet responsible AI, cybersecurity, privacy, IP protection, auditability and ITGC expectations. Partner with Legal, HR, Compliance, Cybersecurity and business leaders on sensitive AI use cases and risk-based controls. Operating Model, COE and Adoption Lead the Data & AI Office as a center of excellence that provides standards, enablement, reusable components and delivery support. Operate a hub-and-spoke model with business AI Champions, process owners and functional teams. Build data literacy and AI adoption through playbooks, coaching, training and practical examples. Recruit, develop and retain a high-performing team across data engineering, analytics, data governance, data science, AI engineering and business analysis. Operations, Budget and Performance Manage the Data & AI budget, vendor relationships, platform consumption and licensing in line with value delivered. Implement portfolio reporting on delivery velocity, adoption, value, risks, data quality and operational performance. Ensure production AI and data capabilities have clear ownership, lifecycle management, monitoring, support and continuous improvement. Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. 10+ years of progressive experience in data, analytics, AI, digital product delivery or related technology leadership roles. Proven track record delivering AI, analytics or data products into production, not only strategy or governance frameworks. Strong working knowledge of data architecture, cloud data platforms, data warehousing, analytics engineering, data governance and information security. Practical understanding of GenAI, LLMs, AI agents, RAG patterns, ML lifecycle, model governance and responsible AI concepts. Ability to lead mixed teams of data engineers, BI/analytics developers, data scientists, AI engineers, business analysts and governance specialists. Excellent executive communication skills, including the ability to translate technical topics into business value, risk and investment decisions. Hands-on technologist with builder mentality Business translator with change management attitude Governance-minded enabler Fluent in English Additional language skills considered an asset Strongly Preferred Experience with Microsoft ecosystem including Azure, Microsoft Fabric, Power BI, Power Platform, Copilot Studio and M365 Copilot. Experience in industrial, manufacturing, engineering, aftermarket, supply chain or complex B2B environments. Experience building or operating an AI Center of Excellence, data office, analytics CoE or hub-and-spoke delivery model. Good understanding of ITGC, SOX-style controls, cybersecurity, privacy and compliance expectations in enterprise environments. Experience with Python, SQL, APIs, data pipelines, MLOps, automation and modern software delivery practices. Husky TechnologiesTM offers a competitive compensation and benefits package and excellent opportunities for growth and advancement. We are committed to equal employment opportunity an...

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