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# Head of Data, AI & Automation (all genders)

- **Company:** Titel
- **Location:** Hamburg, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Cyber Security, Data Architecture, Data Governance, Data Integration, Data Security, Data Systems, Software Deployment, Enterprise Software Applications, AI Platforms, Low-code, Data Management, GXP
- **Published:** September 25, 2026
- **Apply:** https://www.arbeitsagentur.de/jobsuche/jobdetail/10001-1003758157-S

## About the Role

Master's degree in Data Science, Artificial Intelligence, Business Informatics, or a related field.

 - Strong experience in Data platforms and architecture, Automation technologies (RPA, workflow, low-code), AI / advanced analytics
 - Proven track record in Delivering business value (not just technology), Scaling capabilities across complex organizations
 - Ability to: Bridge business and technology, drive change and adoption and operate in regulated environments (GxP is a plus)

## Description

1. Automation as a Value Engine (Primary Focus)

Drive automation across:

 - Discovery & Preclinical Services
 - R&D / Innovation
 - Drug Development
 - Enterprise Platforms (e.g. ERP, Finance, HR)
 - Identify and scale quick-win automation use cases (e.g. RPA in ERP, workflow automation)
 - Establish automation as a standard lever for efficiency and quality improvement
 - Define and track automation-driven value (cost, speed, quality)

 2. Data & AI Platform Leadership

 - Build and operate a scalable enterprise data platform
 - Enable: Data integration across lab, manufacturing and enterprise systems and Self-service analytics and data access
 - Provide the foundation for AI and advanced analytics at scale

 3. AI Enablement & Scaling

 - Move from isolated AI use cases to industrialized AI deployment
 - Define and govern the AI lifecycle (use case * development * scaling)
 - Support: Scientific AI (In Silico, analytics), Operational AI (process optimization, automation)

 4. Domain Enablement (Business Alignment)

Work closely with:

 - Discovery & Preclinical Services
 - R&D / Innovation
 - Manufacturing
 - Enterprise Functions
 - Ensure automation and data solutions are:
 - Business-driven
 - Embedded in workflows
 - Scalable across domains

 5. Governance & Standards

Define standards for:

 - Data architecture
 - Automation tools and platforms
 - AI development and deployment
 - Ensure alignment with:
 - Data governance (business-owned)
 - Security & compliance (InfoSec-defined)


## Related Videos

- [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture)
- [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works)
- [Reimagining app development with Low-code and AI](https://www.wearedevelopers.com/videos/1651-reimagining-app-development-with-low-code-and-ai)
- [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering)
- [What If Apps Built Themselves? AI-Powered Low-Code for the Industrial Enterprise](https://www.wearedevelopers.com/videos/2079-what-if-apps-built-themselves-ai-powered-low-code-for-the-industrial-enterprise)
- [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it)

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