What you'll be doing

• Define and drive the strategic evolution of the team towards building a modern, scalable data platform supporting advanced data and AI use cases.
• Enable development teams to safely and autonomously use data and platform capabilities via tooling, guardrails, and interfaces.
• Establish a long-term roadmap aligning data platform capabilities with AI use cases, product needs, and regulatory constraints.
• Build and grow a high-performing, cross-functional team delivering reliable, scalable, and compliant platform solutions.
• Promote a team culture of initiative, critical thinking, technical leadership, and shared responsibility.
• Coach and develop engineers to enhance skills in data, infrastructure, and platform engineering, raising standards on ownership and delivery.
• Lead performance management to evolve the team towards autonomy, maturity, and high impact.
• Act as liaison between Engineering, Product, Security, and stakeholders to communicate team roadmap and priorities.

Requirements

• Proven experience leading high-impact engineering teams in Platform, Infrastructure, or Machine Learning Engineering, preferably in regulated, complex environments.
• Track record of transforming teams to support long-term strategic goals through skills and mindset development.
• Experience with public cloud providers, ideally AWS, and understanding of cloud-native impacts on data architecture and operations.
• Strong understanding of data platform architectures and trade-offs at scale.
• Familiarity with platform engineering practices including automation, observability, Infrastructure as Code (IaC), and secure-by-default design.
• Leadership skills in people and performance management, with experience coaching and influencing team culture.
• Ability to navigate complex environments balancing speed, reliability, risk, and regulatory constraints.
• Excellent communication and stakeholder management to align engineering, product, and business priorities.
• Strategic thinker able to translate vision into clear plans and team evolution.
• Full professional proficiency in English.

Nice to haves

• Prior exposure to or knowledge of Machine Learning workflows or MLOps lifecycles.
• Experience with AI/ML platform concepts such as feature stores, model deployment patterns, training pipelines, and generative AI.
• Understanding of regulatory constraints relating to platform operations.

Perks and benefits

• Career acceleration by joining a prominent European tech disruptor.
• Competitive benefits including personal development budget, work from home budget, fitness and wellness discounts, language apps, and public transport subsidies.
• Premium subscription on personal N26 bank account plus subscriptions for friends and family.
• Vacation days vary by location, with an additional day of annual leave granted each year of service.
• Opportunity to work on a data platform enabling real AI use cases at scale, with the scope to innovate and shape solutions.
• Relocation package and visa support available for those who require it.