Technical Lead, Data, AI & Analytics (m/f/d)

In this role, you drive the engineering backbone of the BU’s digital initiatives, owning ML/AI apps and the data lake architecture. You act as technical product owner, shaping scalable, production-ready solutions and guiding engineering standards. You’ll bridge solution design with data platforms in an industrial setting, integrating ERP, MES, and plant data. This is an opportunity to lead data-driven transformation and influence how advanced analytics unlocks value in manufacturing.

• competitive compensation and benefits package
• professional development opportunities
• hybrid work model
• global collaboration
• cross-functional teams
• opportunity to impact data-driven transformation

• Refine backlogs and translate business needs into technically scoped work; lead sprint planning with cross-functional owners
• Own architecture for ML/AI apps and digital products, define design principles and reusable patterns
• Apply ML/AI judgment to select appropriate modeling approaches and production requirements
• Design and drive cloud data lake concepts, including data models, ingestion, storage, and access
• Ensure integration with ERP, MES, historians, LIMS, CRM and cloud platform
• Establish engineering standards: code reviews, CI/CD gates, MLOps, model lifecycle management
• Provide technical leadership through mentoring, design reviews, and direction-setting
• Evaluate new technologies (cloud-native data platforms, generative AI, ML tooling) for industrial value

• 8+ years in data science/ML and software engineering
• 3+ years in a technical lead or architect role
• Proven track record delivering production-grade AI/ML systems in industrial contexts
• Hands-on experience with cloud data platforms or data lakes (ideally AWS)
• Advanced Python, cloud-native architecture, containerization, and MLOps
• Experience driving agile delivery with business counterparts
• Fluent understanding of manufacturing IT/OT landscape (ERP, CRM, MES, historians, LIMS)
• Process-industry exposure and experience with hybrid modeling is a plus

• leadership and mentoring
• cross-functional collaboration
• strategic thinking
• AWS cloud platforms
• data lake design and data modeling
• CI/CD and MLOps