ABB AG
.IS Solution Architect(m/w/x)
Full-timeOn-siteExperienced
Mannheim
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FRFreudenberg Technology Innovation SE & Co. KG
Data Architect – Focus on Operations(m/w/x)
Weinheim
Full-timeOn-siteExperienced
Data Science
Nejo AI Summary
Designing and optimizing data models for manufacturing and supply chain. Experience with Azure and ETL processes required. Specialized focus on manufacturing and supply chain data.
Requirements
- Degree in Computer Science or comparable
- Experience as Data Architect or similar
- Knowledge of data modeling and integration
- Experience with Azure and ETL processes
- Understanding of operational processes and data
- Knowledge of CI/CD and DevOps/MLOps
- Analytical skills and collaborative working style
Tasks
- Design and implement scalable data architectures
- Build and maintain data lakes and data warehouses
- Develop and optimize production and logistics data models
- Ensure data quality and integrity across multiple systems
- Integrate streaming and batch data for operational processes
- Select and integrate modern cloud and ETL technologies
- Collaborate with engineers and stakeholders on data solutions
- Establish best practices for cloud architecture and security
- Communicate results to technical and non-technical stakeholders
Work Experience
- approx. 1 - 4 years
Education
- Vocational certificationOR
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- SQL
- NoSQL
- Azure
- Databricks
- CI/CD
- Terraform
- ARM Templates
- DevOps
- MLOps
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Freudenberg Technology Innovation SE & Co. KG and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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FRFreudenberg Technology Innovation SE & Co. KG
Data Architect – Focus on Operations(m/w/x)
Weinheim
Full-timeOn-siteExperienced
Data Science
Nejo AI Summary
Designing and optimizing data models for manufacturing and supply chain. Experience with Azure and ETL processes required. Specialized focus on manufacturing and supply chain data.
Requirements
- Degree in Computer Science or comparable
- Experience as Data Architect or similar
- Knowledge of data modeling and integration
- Experience with Azure and ETL processes
- Understanding of operational processes and data
- Knowledge of CI/CD and DevOps/MLOps
- Analytical skills and collaborative working style
Tasks
- Design and implement scalable data architectures
- Build and maintain data lakes and data warehouses
- Develop and optimize production and logistics data models
- Ensure data quality and integrity across multiple systems
- Integrate streaming and batch data for operational processes
- Select and integrate modern cloud and ETL technologies
- Collaborate with engineers and stakeholders on data solutions
- Establish best practices for cloud architecture and security
- Communicate results to technical and non-technical stakeholders
Work Experience
- approx. 1 - 4 years
Education
- Vocational certificationOR
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- SQL
- NoSQL
- Azure
- Databricks
- CI/CD
- Terraform
- ARM Templates
- DevOps
- MLOps
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Freudenberg Technology Innovation SE & Co. KG and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Freudenberg Technology Innovation SE & Co. KG
Industry
Other
Description
The Freudenberg Group is an equal opportunity employer committed to diversity and inclusion.
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