Data Platform Engineer

Our client is a leading international software provider in the construction and engineering industry. We are currently looking for a "Senior Data Platform Engineer (m/f/d) - NoSQL & Graph Databases" to help shape and operate scalable data architectures beyond traditional relational models. The position is primarily remote within Germany; however, occasional travel for on-site workshops and team meetings is required.

In this role, you will work closely with backend and product teams to design, migrate, and maintain high-performance NoSQL and graph database solutions. You will be part of a central platform engineering team, enabling multiple development teams to leverage modern, robust data infrastructures.

Responsibilities:

• Design, implement, and operate NoSQL and graph database solutions for the central platform
• Own graph data models and query patterns for highly connected, complex domains
• Plan and execute migrations from relational or file-based storage to NoSQL or graph databases
• Collaborate with backend teams to integrate database solutions into new and existing services
• Evaluate and select the right database technologies for different platform and product needs
• Ensure performance, scalability, reliability, and maintainability in production
• Contribute to platform architecture decisions, technical standards, and best practices
• Support and enable product teams through guidance, code reviews, and hands-on collaboration

• Strong hands-on experience with NoSQL and/or graph databases (e.g., Neo4j, Amazon Neptune, MongoDB, or similar)
• Solid understanding of data modeling for graph and non-relational data stores
• Experience in database migration projects and cloud operations (preferably AWS)
• Good knowledge of backend architectures and data access patterns
• Strong problem-solving skills, ownership mindset, and ability to communicate complex technical concepts clearly
• Fluent English; German skills are a plus

Nice to Have: Experience with relational databases, hybrid data architectures, backend technologies (Node.js, .NET, etc.), performance tuning, CI/CD pipelines, DevOps practices, and observability/monitoring of databases

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