BEUMER Group

Data Engineer

BEUMER Group · Shanghai, Shanghai, China

Automation Machinery Manufacturing · 5,001-10,000 employees

8 h ago
Mid (2-5 yrs) Full-time China
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About the role

Build and manage the data foundation to make AI accessible and scalable while integrating enterprise data through APIs and pipelines. Develop and maintain semantic models and data products to ensure high-quality, AI-ready data assets for business consumption.

What they look for

Data Engineering Enterprise Data Integration API Development REST OData Boomi SQL ETL/ELT Snowflake Data Modeling JSON XML Parquet CI/CD DevOps Data Governance

Requirements

Requires a bachelor's degree in computer or data science and at least 3 years of experience in data engineering. Candidates must possess strong expertise in API integration, SQL, ETL/ELT pipelines, and modern data platform architectures like Snowflake.

Full description

Company Description

BEUMER Group is a leader in the engineering and manufacturing of high-tech intralogistic systems for global markets. Our employees differentiate themselves by their ability to provide innovative solutions to our customers that incorporates a high-level of industry knowledge and a strong commitment to consistently and continuously expand their skills and knowledge. We fully support these high standards through a supportive teamwork structure, a mutual respect, and a working culture based on trust that fosters stability and security for all of our employees. 

Job Description

Job Responsibility: 

  • Build and manage the data foundation that makes AI accessible and scalable across the organization.
  • Enable seamless integration of enterprise data through APIs, middleware, and data pipelines.
  • Deliver trusted, high-quality, and AI-ready data assets for analytics, automation, and AI solutions.
  • Create scalable data products, semantic models, and integration frameworks that simplify data consumption.
  • Connect business applications, platforms, and external services to provide unified and accessible enterprise data. 
  • Design, develop, and maintain enterprise data integrations and API-based data exchange.
  • Build and operate scalable data pipelines that provide reliable access to business-critical data.
  • Integrate ERP, CRM, HR, Finance, Manufacturing, and external systems into the enterprise data platform.
  • Manage and optimize data ingestion, transformation, and delivery processes.
  • Develop and maintain semantic models that make data understandable and consumable for AI and business users.
  • Ensure data quality, lineage, consistency, and governance across integrated systems.
  • Create reusable integration patterns, data products, and data services.
  • Monitor, troubleshoot, and continuously improve integration and pipeline performance.
  • Support reporting, analytics, automation, and AI initiatives with trusted and accessible datasets.
  • Collaborate with business stakeholders to identify and prioritize data integration opportunities.
  • Contribute to the evolution of the enterprise data architecture and AI data platform roadmap.
  • Maintain technical documentation, standards, and best practices for integrations and data assets.

Qualifications

Job Requirements:

  • Bachelor's degree with majored in computer or data science or similar field. 
  • > 3 years experience in data engineering / science. 
  • Strong experience in Data Engineering and Enterprise Data Integration.
  • Expertise in API development and integration (REST, OData).
  • Experience with Boomi or similar Integration Platform-as-a-Service (iPaaS) solutions.
  • Advanced SQL and data transformation skills.
  • Experience designing and operating ETL/ELT pipelines.
  • Knowledge of Snowflake or similar database and/or data lake solutions.
  • Understanding of data lake, data warehouse, and modern data platform architectures.
  • Experience with semantic data modeling and business data abstraction layers.
  • Knowledge of JSON, XML, Parquet and further common data formats.
  • Experience with source control, CI/CD, and DevOps practices.
  • Understanding of data governance, security, privacy, and compliance principles.
  • Experience supporting AI and machine learning use cases through data engineering.
  • Familiarity with event-driven architectures, messaging, and real-time data integration.
  • Passion for making data accessible, understandable, and usable for AI and business value creation.
  • Strong analytical and systems-thinking capabilities.
  • Ability to translate complex business requirements into scalable data solutions.
  • Strong stakeholder engagement and communication skills.
  • Collaborative mindset with the ability to work across business and technology functions.
  • Ownership mentality with accountability for end-to-end data solutions.
  • Strong problem-solving and troubleshooting capabilities.
  • Curiosity for emerging AI, data, and integration technologies.