Digital data analyst Jobs in Dietikon

Job Description

We are looking for a skilled and motivated Data Platform / DevOps Engineer to operate and evolve our Global Data Platform. In 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

Requirements

We are looking for a skilled and motivated Data Platform / DevOps Engineer to operate and evolve our Global Data Platform. In 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