Senior Data Platform DevOps Engineer (Agile, Digital Platforms)

Zürich - Switzerland

Monthly Salary: Not Disclosed

Posted on: 6 hours ago

Vacancies: 1 Vacancy

Job Summary

We are looking for a skilled and motivated Data Platform / DevOps Engineer to operate and evolve our Global Data this role you will work with modern distributed systems and data technologies ensuring reliable secure and scalable data pipelines. You will apply Agile and DevSecOps principles to continuously improve platform stability automation and delivery efficiency while collaborating closely with security engineering and cloud operations teams.

Key Responsibilities

Operate and maintain Global Data Platform components including:
- VM servers Kubernetes clusters and Kafka
- Data and analytics applications such as Apache stack Collibra Dataiku and similar tools
Design and implement automation for:
- Infrastructure provisioning
- Security components
- CI/CD pipelines supporting ELT/ETL data workflows
Build resiliency into data pipelines through:
- Platform health checks
- Monitoring and alerting mechanisms
- Proactive issue prevention and recovery strategies
Apply Agile and DevSecOps practices to deliver integrated solutions in iterative increments
Collaborate and liaise with:
- Enterprise Security
- Digital Engineering
- Cloud Operations teams
Review system issues incidents and alerts to:
- Perform root cause analysis
- Drive long-term fixes and platform improvements
Stay current with industry trends emerging technologies and best practices in data platforms and DevOps

Requirements

Minimum 5 years of experience designing and supporting large-scale distributed systems
Hands-on experience with:
- Streaming and file-based ingestion (e.g. Kafka Control-M AWA)
- DevOps and CI/CD tooling (e.g. Jenkins Octopus; Ansible Chef XL tools are a plus)
Experience with on-premises Big Data architectures; cloud migration experience is an advantage
Integration of Data Science workbenches (e.g. Dataiku or similar)
Practical experience working in Agile environments (Scrum SAFe)
Supporting enterprise reporting and data science use cases

Technical Skills

Strong knowledge of modern data architectures:
- Data lakes Delta Lakes Data Meshes and data platforms
Experience with distributed and cloud-native technologies:
- S3 Parquet Kafka Kubernetes Spark
Programming and scripting skills:
- Python (required)
- Java / Scala / R
- Linux scripting Jinja Puppet
Infrastructure and platform engineering:
- VM setup and administration
- Kubernetes scaling and operations
- Docker Harbor
- CI/CD pipelines
- Firewall rules and security controls

Required Skills:

We are looking for a skilled and motivated Data Platform / DevOps Engineer to operate and evolve our Global Data this role you will work with modern distributed systems and data technologies ensuring reliable secure and scalable data pipelines. You will apply Agile and DevSecOps principles to continuously improve platform stability automation and delivery efficiency while collaborating closely with security engineering and cloud operations teams. Key Responsibilities Operate and maintain Global Data Platform components including: VM servers Kubernetes clusters and Kafka Data and analytics applications such as Apache stack Collibra Dataiku and similar tools Design and implement automation for: Infrastructure provisioning Security components CI/CD pipelines supporting ELT/ETL data workflows Build resiliency into data pipelines through: Platform health checks Monitoring and alerting mechanisms Proactive issue prevention and recovery strategies Apply Agile and DevSecOps practices to deliver integrated solutions in iterative increments Collaborate and liaise with: Enterprise Security Digital Engineering Cloud Operations teams Review system issues incidents and alerts to: Perform root cause analysis Drive long-term fixes and platform improvements Stay current with industry trends emerging technologies and best practices in data platforms and DevOps

Key Responsibilities

Operate and maintain Global Data Platform components including:
- VM servers Kubernetes clusters and Kafka
- Data and analytics applications such as Apache stack Collibra Dataiku and similar tools
Design and implement automation for:
- Infrastructure provisioning
- Security components
- CI/CD pipelines supporting ELT/ETL data workflows
Build resiliency into data pipelines through:
- Platform health checks
- Monitoring and alerting mechanisms
- Proactive issue prevention and recovery strategies
Apply Agile and DevSecOps practices to deliver integrated solutions in iterative increments
Collaborate and liaise with:
- Enterprise Security
- Digital Engineering
- Cloud Operations teams
Review system issues incidents and alerts to:
- Perform root cause analysis
- Drive long-term fixes and platform improvements
Stay current with industry trends emerging technologies and best practices in data platforms and DevOps

Requirements

Minimum 5 years of experience designing and supporting large-scale distributed systems
Hands-on experience with:
- Streaming and file-based ingestion (e.g. Kafka Control-M AWA)
- DevOps and CI/CD tooling (e.g. Jenkins Octopus; Ansible Chef XL tools are a plus)
Experience with on-premises Big Data architectures; cloud migration experience is an advantage
Integration of Data Science workbenches (e.g. Dataiku or similar)
Practical experience working in Agile environments (Scrum SAFe)
Supporting enterprise reporting and data science use cases

Technical Skills

Strong knowledge of modern data architectures:
- Data lakes Delta Lakes Data Meshes and data platforms
Experience with distributed and cloud-native technologies:
- S3 Parquet Kafka Kubernetes Spark
Programming and scripting skills:
- Python (required)
- Java / Scala / R
- Linux scripting Jinja Puppet
Infrastructure and platform engineering:
- VM setup and administration
- Kubernetes scaling and operations
- Docker Harbor
- CI/CD pipelines
- Firewall rules and security controls