Data Engineer

BEUMER Group beumergroup.com Open · verified Oct 24, 2026

On-site Qingpu Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at BEUMER Group. Qingpu · full-time.

Pay not stated Data Engineer salary

RoleData Engineering

SeniorityMid-level

LocationQingpu

WorkplaceOn-site

EmploymentFull-time

PostedAug 3, 2026 · 2mo ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build and run data pipelines and API integrations that connect business-critical systems to the enterprise data platform
Shape ingestion, transformation and delivery so datasets are dependable for analytics, automation and AI use
Create semantic models and reusable data products that help business and AI users work with enterprise data
Track data quality, lineage and integration performance, then resolve issues and improve reliability
Work with business stakeholders to prioritize integration needs and contribute to data architecture plans

What you bring

A computer or data science degree, or a similar field, plus more than three years in data engineering or science
Strong data engineering and enterprise integration experience, including REST or OData APIs and an iPaaS such as Boomi
Advanced SQL skills, data transformation experience, and a record of designing and operating ETL or ELT pipelines
Experience with Snowflake or a comparable data store, semantic modeling, and data platform architectures

Who this fits

This role suits a mid-level data engineer who can turn complex business needs into scalable integrations and usable data assets. You’ll work onsite in Qingpu and collaborate across business and technology teams.

From the employer

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 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.

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.