Workday HCM Senior Consultant

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Infoplus Technologies GmbH
flag_no Deutschland
Vinita Sharma

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Fashion of hiring : Fixed Term Contract for 1 year
Job ID: VS-
Work location: Wiesbaden, Germany
Language: -B1 German and English

Job Details
Data and Analytics Quality Engineer

This role will be responsible for developing, designing, engineering, and scaling manufacturing statistical process control analytics models with the aim of improving manufacturing quality, yield and overall efficiency. The Quality Engineer will be deploying solutions to support different ZF products and business units across the globe, interfacing with manufacturing and engineering teams. Responsibility will cover the complete lifecycle of analysis, from initial data engineering, discovering solutions that target customer KPI’s, recommending actions that drive value and transition of knowledge to the local team.
The Quality Engineer could work in multiple different ZF manufacturing locations to identify key manufacturing process and test steps that can be optimized using analytics, including statistical process control models.
To be successful in this role, you should have previous experience in discrete manufacturing environments, in either a quality or manufacturing role. The ideal candidate will combine experience from a technical environment with a strong understanding of modern analytical methods, and experience of a big data environment.

• Leading analytical analysis and coordination within manufacturing plant quality improvement projects.
• Analyzes quality data from plant processes or customer indicators, by employing hypothesis, normal distribution, and process capability analysis tests.
• Performing statistical analyses using probability, multiple regression, experimental design, hypothesis testing, and confidence bounds / tolerance limits.
• Developing process control models based on series, parallel, and complex models
• Responsibility for realizing stated objectives for quality and yield improvement
• Perform statistical analysis to identify interdependencies among different process parameters (upstream and downstream) and their impact on yield.
• Recommends improvement to existing quality or production parameters to achieve optimum quality within limits of equipment capability.

• Knowledge transfer and training of local plant team, once a stable
• Excellent communication skills and the ability to communicate statistical concepts to non-technical audiences

• Technical leadership in statistical quality control, lean manufacturing concepts, and six-sigma tools and analyses.
• Demonstrated experience working in manufacturing statistical process control or equivalent
• Demonstrated capability to communicate findings, orally and visually, to senior leadership members and outside partners and customers in the technology
ecosystem along with the ability to effectively collaborate with cross functional teams
• Deep technical understanding of statistics as well as a demonstrated track record of application of these methods to achieve documented results, (could include
mean time before failure, Weibull 3-parameter distribution, reliability modeling, and reliability demonstration tests).
• Able to develop quality improvement experiments by applying full and fractional factorial techniques
• Experience with sampling plans through attribute, variable, and sequential sampling methods.
• Understand statistical process controls by applying demerit/unit, zone charting, X2 charts for distributions and individual-media/range for multi-stream
• Minimum of 10 years of experience working in manufacturing process engineering in various manufacturing processes
• Knowledge and application of industrial quality standards and methods, including Quality Systems (ISO 16949), APQP, FMEA, MSA, SPC, 8D, 6-Sigma.
• Working knowledge of process engineering software packages
• Strong time management skills to support multiple projects simultaneously to meet short sprints
• Excellent communication skills along with the ability to effectively collaborate with cross functional teams
• Bachelors or Masters in Engineering, Manufacturing, Computer Science or similar field
• Speak and read German to an intermediate level, capable of interacting with colleagues in their native language.
• Ability to travel to multiple ZF sites in Europe

Mit freundlichen Grüßen / Regards,
Vinita Sharma

Infoplus Technologies GmbH
14th Floor, Tower 185
Friedrich-Ebert-Anlage 35-37
60327 Frankfurt am Main

Tel: +49 (0)