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Huzzle Ltd

Data Engineer

Posted 5 Days Ago
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In-Office
Berlin
Mid level
In-Office
Berlin
Mid level
Design and build a scalable data layer for an AI-powered SAP consulting system. Own metadata architecture, develop pipelines ingesting SAP telemetry and consulting insights, and collaborate with AI/ML teams to provide high-quality signals for training and inference while ensuring data integrity, versioning, and long-term scalability.
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About Huzzle

At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI.

Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team.

Job Type: Full-time

Location: On-site in Berlin, Germany

About the Company

Our client is an ambitious, venture-backed startup building an AI-powered SAP consultant designed to transform how enterprise systems are implemented and optimized. Already post-revenue and working with DAX 40 and Fortune 500 companies. Their mission is to encode and compound consulting knowledge across deployments, creating a system that becomes smarter with every customer engagement.

Job Summary

We are hiring an AI Data Engineer to design and build the foundational data layer that powers a next-generation AI system for SAP consulting. This role is critical in structuring complex enterprise data—capturing configurations, decisions, and relationships across deployments—and transforming it into scalable, queryable knowledge that improves model accuracy over time.

You will work at the intersection of data engineering and AI, ensuring that structured insights flow seamlessly into machine learning systems and continuously evolve with each customer interaction.

Key Responsibilities
  • Design and build a scalable data layer that maps relationships across SAP projects, including configurations, outcomes, and domain patterns
  • Own the metadata architecture, including data labeling, linking, versioning, and queryability
  • Develop robust data pipelines to ingest SAP telemetry and consulting insights into structured datasets
  • Collaborate closely with AI/ML teams to provide high-quality signals for model training and inference
  • Continuously refine and improve data systems with each customer deployment
  • Ensure high standards of data integrity, consistency, and usability across systems
  • Architect systems with a long-term, scalable mindset rather than short-term fixes

Requirements
  • Strong background in data engineering, including pipeline development, schema design, and data modeling
  • Experience working with complex, semi-structured enterprise data
  • Knowledge of graph-based systems (knowledge graphs, graph databases) or relational modeling for complex domains
  • Systems-level thinking with a focus on architecture and scalability
  • Proven ability to maintain high standards for data quality and reliability
  • Willingness to work on-site in Berlin (mandatory requirement)

Benefits

💰 Competitive salary aligned with top-tier European startup benchmarks

🌍 Work on-site in Berlin at a fast-growing, venture-backed AI company

📈 High-growth environment with strong funding and enterprise traction

🤝 Collaborate with elite engineers, AI researchers, and enterprise clients

🧠 Exposure to cutting-edge AI, data systems, and enterprise-scale challenges

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