V
Vivenu
Data Engineering Lead (Agentic Infrastructure)
Skills
Data EngineeringData AnalysisMachine LearningAI
2 months ago
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Important information
Contract type:
Permanent
Location:
40 Düsseldorf, Germany
Work mode:
Onsite
Published on:
12 August 2026
What they need
- As a Data Engineering Lead, Agentic Infrastructure, you will be the foundational technical leader of our data organization, guiding a dedicated pod of engineers in the future. You will act as the technical authority and central hub for all data initiatives across the company, ensuring a cohesive, secure, and scalable data strategy
- By building this scalable technical foundation, you will pave the way for company-wide AI adoption. As the internal platform matures, your scope will likely expand to drive robust data and AI capabilities directly into our customer-facing products
- Build the foundation: Design, architect, and build our highly scalable internal data platform and core data warehouse, centralizing data across all internal tools and systems. Ensure that every data initiative goes through your team and aligns with our overarching architecture and scalability standards
- Lead & mentor: Provide technical leadership, architectural guidance, and hands-on mentorship to a high-impact team of engineers
- Drive company-wide AI adoption: Build the robust, reliable data pipelines and infrastructure required to power our internal AI initiatives, enabling intelligent tooling and automation
- Scale for the future: Establish a future-proof technical foundation that initially optimizes internal operations, with a clear roadmap to expand into core product features
- Establish operational excellence: Implement data governance, data lineage, observability, and strict quality controls to ensure the data platform is reliable and trusted- Familiarity or hands-on experience with Agentic AI technologies, specifically building infrastructure where autonomous agents and AI models can learn, access data, and execute tasks
- 8+ years of hands-on experience in Data Engineering, building modern data stacks, central data warehouses, and high-throughput data pipelines
- Excellent communication skills with the ability to partner with internal stakeholders to centralize and streamline all business data requests
- Proven ability to design company-wide data architectures and act as the principal technical decision-maker for complex data systems
- Strong understanding of how to structure, model, and pipeline data specifically to support AI, machine learning, and advanced analytics adoption
- A track record of technically leading and elevating small teams while remaining deeply hands-on
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