Zühlke Engineering AG
Senior Data Engineer(m/w/x)
Vollzeitmit HomeofficeSenior
Schlieren
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Senior Data Engineer – ML Data Platform(m/w/x)
Zürich
Vollzeitmit HomeofficeSenior
AI/ML
Nejo KI-Zusammenfassung
Designing and optimizing scalable data pipelines for ML training data infrastructure. 5+ years in data engineering, with ML system datasets and cloud platforms experience required. Direct impact on ML training data infrastructure evolution.
Anforderungen
- 5+ years professional experience in data engineering, ML infrastructure, or related fields
- Strong experience designing large-scale data pipelines
- Strong experience building distributed data processing systems
- Solid experience with cloud-based data platforms and storage systems (Azure or similar)
- Experience with ML system datasets, ideally multimodal data
- Strong programming skills in Python
- Familiarity with modern data engineering tools and workflows
- Experience with high-volume data ingestion
- Experience with data processing pipelines
- Experience with dataset versioning
- Beneficial familiarity with robotics data pipelines or ROS2-based ecosystems
- Strong problem-solving skills
- Effective collaboration with cross-functional technical teams
Aufgaben
- Design, build, and maintain scalable data pipelines
- Manage data collection, annotation, quality, governance, and storage
- Develop and optimize infrastructure for ML training data
- Contribute to cloud data platform design and evolution
- Manage data ingestion pipelines
- Develop data labeling workflows
- Implement dataset cataloging and versioning
- Ensure data compliance
- Implement processes and tooling for data quality
- Enhance data reliability and observability
- Collaborate with research and engineering teams
- Support creation of large-scale datasets
- Manage large-scale datasets for ML models
- Support data collection and integration from robotics
- Support data collection and integration from sensor systems
- Manage data workflows using ROS2 frameworks
- Contribute to data engineering best practices
- Contribute to documentation best practices
- Contribute to testing best practices
- Contribute to reproducible data pipelines
Berufserfahrung
- 5 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Azure
- Python
- ROS2
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Consulteer erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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COConsulteer
Senior Data Engineer – ML Data Platform(m/w/x)
Zürich
Vollzeitmit HomeofficeSenior
AI/ML
Nejo KI-Zusammenfassung
Designing and optimizing scalable data pipelines for ML training data infrastructure. 5+ years in data engineering, with ML system datasets and cloud platforms experience required. Direct impact on ML training data infrastructure evolution.
Anforderungen
- 5+ years professional experience in data engineering, ML infrastructure, or related fields
- Strong experience designing large-scale data pipelines
- Strong experience building distributed data processing systems
- Solid experience with cloud-based data platforms and storage systems (Azure or similar)
- Experience with ML system datasets, ideally multimodal data
- Strong programming skills in Python
- Familiarity with modern data engineering tools and workflows
- Experience with high-volume data ingestion
- Experience with data processing pipelines
- Experience with dataset versioning
- Beneficial familiarity with robotics data pipelines or ROS2-based ecosystems
- Strong problem-solving skills
- Effective collaboration with cross-functional technical teams
Aufgaben
- Design, build, and maintain scalable data pipelines
- Manage data collection, annotation, quality, governance, and storage
- Develop and optimize infrastructure for ML training data
- Contribute to cloud data platform design and evolution
- Manage data ingestion pipelines
- Develop data labeling workflows
- Implement dataset cataloging and versioning
- Ensure data compliance
- Implement processes and tooling for data quality
- Enhance data reliability and observability
- Collaborate with research and engineering teams
- Support creation of large-scale datasets
- Manage large-scale datasets for ML models
- Support data collection and integration from robotics
- Support data collection and integration from sensor systems
- Manage data workflows using ROS2 frameworks
- Contribute to data engineering best practices
- Contribute to documentation best practices
- Contribute to testing best practices
- Contribute to reproducible data pipelines
Berufserfahrung
- 5 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Azure
- Python
- ROS2
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Consulteer erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Über das Unternehmen
Consulteer
Branche
IT
Beschreibung
The company delivers performant, reusable assets and pipelines for advanced simulation and robotics systems.
Noch nicht perfekt?
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