Contribute to the future of Mercedes-Benz in China by leading the charge in AI innovation – build innovative solutions, drive rapid prototypes, and scale AI to new heights. As part of the AI&Data Value team, the position is responsible to help our organization to transform into an AI-driven enterprise by designing and implementing a graph based knowledge management platforms that unifies data across domains.
As a Data Engineer in the team you will…
Build and maintain ETL/ELT pipelines to ingest structured and unstructured data into centralized knowledge graph platforms
Design, develop and maintain semantic data models that represent heterogeneous systems (ERP, CRM, IoT) in a knowledge graph.
Implement and optimize database instances for graph storage and querying.
Apply mapping scripts and validation rules to ensure governance compliance and data quality.
Optimize graph queries and graph-based reasoning for large-scale automotive datasets.
Collaborate on cloud/hybrid deployments (Azure, AWS, Alibaba Cloud) for scalability and resilience.
Work closely with AI architects, data scientists, and business stakeholders to align the technical design with use-case requirements.
Participate in sprint planning and architecture.
Monitor system performance, troubleshoot issues, and implement optimizations to keep our data flowing smoothly.
Research and implement new data technologies and best practices to keep our data platform cutting-edge.
Bachelor or Master’s in a quantitative degree (Computer Science, Information Systems, Engineering, Physics, Maths) or equivalent professional experience
Experience:
5+ years in data engineering
Ideally experience in semantic technologies and graph database design
Hands-on experience with GraphDB, Neo4j or other equivalent software
Fluent in Python & SQL, RESTful APIs and web scraping for data pipelines and automation.
Further proficiency in Java, or Scala or similar
Familiarity with RDF representation beneficial
Familiarity with ETL frameworks (Spark especially) and cloud data platforms (Databricks).
Experience with data warehousing concepts, dimensional modeling, and big data technologies
Ability to design, document and optimize complex data architectures
Experience in integrating data solutions into existing business processes and IT landscapes, including interface management and deployment
Familiarity with sprint-based development, CI/CD and associated tooling (JIRA, Confluence, Github etc…)
Specific Knowledge
Abstract thinking and problem-solving for complex data relationships.
Fluent in English and Chinese
Exceptionally good communication skills towards colleagues and management
Excellent written and communications skills to report back the findings in a clear, structured manner are required
