Manager Data & AI Engineering [T500-21798]

About the company for Stolt Nielsen:

Stolt-Nielsen is a family-founded global leader in bulk-liquid and chemical logistics, transportation, and storage, known for its commitment to safety, service excellence, and innovation. At the Stolt-Nielsen Digital Innovation Centre, we bring this legacy into the future building smarter systems, driving digital transformation, and shaping what's next for the world of logistics. Here, youre encouraged to think boldly, challenge convention, and help move todays products toward tomorrows possibilities.

About the Role:

As an Engineering Manager Data and AI, you will lead and grow a world-class engineering team within our Digital Innovation Centre. You will shape and nurture a team of specialists who deliver cutting-edge solutions for our business units, while fostering a culture of quality, collaboration, and continuous learning.

In this role, you are not directly assigned to project delivery but instead oversee the engineering discipline (vertical) in a matrix organization. Your engineers will collaborate with various business-aligned product and project teams, while you focus on capability building, mentoring, demand management, and ensuring alignment to technical and quality standards. In this all, you will collaborate with a Domain Architect Data and AI, who will act as your technical peer.

You will also drive cross-functional initiatives such as process improvement, skill development, and technology adoption to continuously elevate our engineering maturity and impact.

At Stolt-Nielsen, we take Digital seriously. As we are further building up our engineering practice, there is ample room for you to contribute, take initiative and shape the future of our ways of working and technology landscape.

What Youll Do:

• Build, coach, and develop a high-performing engineering team with deep expertise in Data and AI
• Manage staffing, development, and career growth for engineers across multiple projects and teams.
• Oversee and prioritize the engineering backlog for your vertical (e.g., tools, frameworks, shared components, reusable assets).
• Collaborate with Architecture, DevOps, and Product leadership to ensure consistent delivery standards and best practices.
• Support innovation and experimentation within your area staying current with emerging technologies and methodologies.
• Define and measure quality, productivity, and engagement metrics for your engineering discipline.
• Foster a culture of collaboration, ownership, and continuous improvement.
• Partner with HR and leadership to drive recruitment, onboarding, and employee engagement.
• Contribute to strategic discussions around technology choices, skill development, and long-term digital capability building.

What Youll Bring:

• Proven leadership experience in managing technical teams and engineering talent.
• Strong background in data engineering, data science, or analytics, with the ability to understand and guide technical discussions.
• Experience with tools such as Databricks, Python, Spark, Power BI, SQL, and ML and Generative AI frameworks/concepts.
• Understanding of data governance, MLOps, and data platform architectures.
• Familiarity with AI/ML pipelines and model lifecycle management.
• Experience in modern engineering practices such as Agile/Scrum, CI/CD, DevOps, test automation, and cloud-native development.
• Excellent communication and stakeholder management skills; able to bridge between business and technical teams.
• Passion for mentoring, growing people, and building a thriving team culture.
• Strategic mindset with an operational discipline; you balance innovation with delivery excellence.
• Enthusiasm for learning, improvement, and empowering others.

Must Have Skills:

• 10+ years of relevant industry experience, including 3+ years in an engineering management or people leadership role.
• Deep understanding of software engineering principles, agile delivery, and technical quality management.
• Hands-on familiarity with modern cloud and DevOps ecosystems (Azure preferred) & AI/ML pipelines and model lifecycle management.
• Strong interpersonal and leadership skills, able to inspire and build trust.
• Fluent in English (spoken and written)