Asks for

The ad says“Data Architecture Mastery: Solid understanding of data warehouse design concepts and structural implementation using ETL/ELT workflow tools (Airflow, DataX, Kettle).”
The ad says“Core Technical Expertise: Mastery of SQL with deep, practical experience leveraging distributed query engines (Hive, Presto, ClickHouse).”
The ad says“Statistical Competency: Practical knowledge of statistical methods, including hypothesis testing, regression analysis, and clustering algorithms.”
The ad says“Data Architecture Mastery: Solid understanding of data warehouse design concepts and structural implementation using ETL/ELT workflow tools (Airflow, DataX, Kettle).”
The ad says“Data Architecture Mastery: Solid understanding of data warehouse design concepts and structural implementation using ETL/ELT workflow tools (Airflow, DataX, Kettle).”
The ad says“Analytical Toolkit: High proficiency in Python data analysis libraries (Pandas, NumPy, Matplotlib) and advanced Microsoft Excel functionalities.”
The ad says“Core Technical Expertise: Mastery of SQL with deep, practical experience leveraging distributed query engines (Hive, Presto, ClickHouse).”
The ad says“Statistical Competency: Practical knowledge of statistical methods, including hypothesis testing, regression analysis, and clustering algorithms.”
The ad says“Data Architecture Mastery: Solid understanding of data warehouse design concepts and structural implementation using ETL/ELT workflow tools (Airflow, DataX, Kettle).”
The ad says“Analytical Toolkit: High proficiency in Python data analysis libraries (Pandas, NumPy, Matplotlib) and advanced Microsoft Excel functionalities.”
The ad says“Analytical Toolkit: High proficiency in Python data analysis libraries (Pandas, NumPy, Matplotlib) and advanced Microsoft Excel functionalities.”
The ad says“Analytical Toolkit: High proficiency in Python data analysis libraries (Pandas, NumPy, Matplotlib) and advanced Microsoft Excel functionalities.”
The ad says“Core Technical Expertise: Mastery of SQL with deep, practical experience leveraging distributed query engines (Hive, Presto, ClickHouse).”
The ad says“Analytical Toolkit: High proficiency in Python data analysis libraries (Pandas, NumPy, Matplotlib) and advanced Microsoft Excel functionalities.”
The ad says“Statistical Competency: Practical knowledge of statistical methods, including hypothesis testing, regression analysis, and clustering algorithms.”
The ad says“Core Technical Expertise: Mastery of SQL with deep, practical experience leveraging distributed query engines (Hive, Presto, ClickHouse).”
The ad says“Statistical Competency: Practical knowledge of statistical methods, including hypothesis testing, regression analysis, and clustering algorithms.”

Job Responsibilities

Architect Operational Technology (OT) Data Pipelines: Design, build, and optimize high-availability data acquisition, ingestion, and preprocessing systems for industrial on-site (OT) equipment and IoT sensors.
Advance Data Warehousing: Develop and maintain scalable, robust enterprise data models utilizing advanced dimensional and normalized data modeling methodologies.
Drive Big Data Analytics: Conduct complex data analysis and build interactive reporting solutions utilizing high-performance query engines, including Hive, Presto, and ClickHouse.
Enable Data-Driven Decisions: Apply statistical analysis techniques to extract actionable insights from manufacturing datasets, delivering comprehensive analytical reports to support strategic business decisions.
Ensure Data Governance: Establish data quality standards, monitor pipeline performance, and troubleshoot data anomalies to guarantee data integrity across the production floor.

Qualifications

Academic Background: Bachelor’s degree or higher in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field.
Proven Track Record: Minimum of 2–3 years of hands-on experience in big data development, data engineering, or large-scale data pipeline projects.
Core Technical Expertise: Mastery of SQL with deep, practical experience leveraging distributed query engines (Hive, Presto, ClickHouse).
Analytical Toolkit: High proficiency in Python data analysis libraries (Pandas, NumPy, Matplotlib) and advanced Microsoft Excel functionalities.
Data Architecture Mastery: Solid understanding of data warehouse design concepts and structural implementation using ETL/ELT workflow tools (Airflow, DataX, Kettle).
Statistical Competency: Practical knowledge of statistical methods, including hypothesis testing, regression analysis, and clustering algorithms.
Industry Advantage: Prior experience in manufacturing execution systems (MES), industrial IoT (IIoT) data architecture, or PLC/SCADA data integration is highly preferred.

Come join our global, inclusive & diverse team

Our purpose is to improve the quality of life of everyone we touch through our innovative motion systems. We are a truly global team bound together by our shared values. Our culture is built on the diversity, knowledge, skills, creativity, and talents that each employee brings to the company. Our people are our company’s most valuable asset. We are committed to providing an inclusive, diverse and equitable workplace where employees of different backgrounds feel valued and respected, regardless of their age, gender, race, ethnicity or religious background. We are committed to inspiring our employees to grow, act with ownership and find fulfilment and meaning in the work they do.

欢迎加入我们全球性、富包容和多元化的团队！

我们的目标是通过创新的驱动系统提高每一个产品接触者的生活质量。我们是一个真正的全球性团队，我们有着共同的价值观因而联结在一起。我们的文化是建基于每一位员工为公司带来的多样性、知识、技能、创意和才能之上。我们的员工是我们企业最宝贵的资产。我们致力于为员工提供一个包容、多元和平等的工作场所，在这里无论他们的年龄、性别、肤色、种族或宗教信仰如何，不同背景的员工都能感到受重视和尊重。我们致力于激励我们的员工成长，以主人翁精神行事，并在他们所做的工作中找到成就感和意义。

Asks for

Values